2014

• P. Arroba, J. L. Risco-Martín, M. Zapater, J. M. Moya, and J. L. Ayala, "Enhancing regression models for complex systems using evolutionary techniques for feature engineering," Journal of grid computing, 2014. doi:10.1007/s10723-014-9313-8
  [BibTeX] [Abstract] [Download PDF]
  

  This work proposes an automatic methodology for modeling complex systems. Our methodology is based on the combination of Grammatical Evolution and classical regression to obtain an optimal set of features that take part of a linear and convex model. This technique provides both Feature Engineering and Symbolic Regression in order to infer accurate models with no effort or designer's expertise requirements. As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. These facilities consume from 10 to 100 times more power per square foot than typical office buildings. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. For this case study, our methodology minimizes error in power prediction. This work has been tested using real Cloud applications resulting on an average error in power estimation of 3.98 \%. Our work improves the possibilities of deriving Cloud energy efficient policies in Cloud data centers being applicable to other computing environments with similar characteristics.

  @article{ARZ+14b,
  abstract = {This work proposes an automatic methodology for modeling complex systems. Our methodology is based on the combination of Grammatical Evolution and classical regression to obtain an optimal set of features that take part of a linear and convex model. This technique provides both Feature Engineering and Symbolic Regression in order to infer accurate models with no effort or designer's expertise requirements. As advanced Cloud services are becoming mainstream, the contribution of data centers in the overall power consumption of modern cities is growing dramatically. These facilities consume from 10 to 100 times more power per square foot than typical office buildings. Modeling the power consumption for these infrastructures is crucial to anticipate the effects of aggressive optimization policies, but accurate and fast power modeling is a complex challenge for high-end servers not yet satisfied by analytical approaches. For this case study, our methodology minimizes error in power prediction. This work has been tested using real Cloud applications resulting on an average error in power estimation of 3.98 \%. Our work improves the possibilities of deriving Cloud energy efficient policies in Cloud data centers being applicable to other computing environments with similar characteristics.},
  author = {Arroba, Patricia and Risco-Mart\'{\i}n, Jos\'{e} L. and Zapater, Marina and Moya, Jos\'{e} M. and Ayala, Jos\'{e} L.},
  citeulike-article-id = {13379223},
  citeulike-linkout-0 = {http://dx.doi.org/10.1007/s10723-014-9313-8},
  doi = {10.1007/s10723-014-9313-8},
  issn = {1570-7873},
  journal = {Journal of Grid Computing},
  keywords = {dc, greenlsi, josem},
  month = sep,
  posted-at = {2014-10-04 17:51:59},
  priority = {2},
  title = {Enhancing Regression Models for Complex Systems Using Evolutionary Techniques for Feature Engineering},
  url = {http://dx.doi.org/10.1007/s10723-014-9313-8},
  year = {2014}
  }

• P. Arroba, J. L. Risco-Martín, M. Zapater, J. M. Moya, J. L. Ayala, and K. Olcoz, "Server power modeling for Run-Time energy optimization of cloud computing facilities," in International conference on sustainability in energy and buildings, 2014. doi:10.1016/j.egypro.2014.12.402
  [BibTeX] [Download PDF]

  @inproceedings{ARZ+14,
  author = {Arroba, Patricia and Risco-Mart\'{\i}n, Jos\'{e} L. and Zapater, Marina and Moya, Jos\'{e} M. and Ayala, Jos\'{e} L. and Olcoz, Katzalin},
  booktitle = {International Conference on Sustainability in Energy and Buildings},
  citeulike-article-id = {13166637},
  citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.egypro.2014.12.402},
  doi = {10.1016/j.egypro.2014.12.402},
  keywords = {ee, greendisc, greenlsi, josem},
  posted-at = {2014-10-03 18:42:45},
  priority = {2},
  title = {Server Power Modeling for {Run-Time} Energy Optimization of Cloud Computing Facilities},
  url = {http://dx.doi.org/10.1016/j.egypro.2014.12.402},
  year = {2014}
  }

• M. Zapater, J. L. Ayala, and J. M. Moya, "Proactive and reactive thermal aware optimization techniques to minimize the environmental impact of data centers," in Design automation conference, 2014.
  [BibTeX]

  @inproceedings{ZAM14,
  author = {Zapater, Marina and Ayala, Jose L. and Moya, Jose M.},
  booktitle = {Design Automation Conference},
  citeulike-article-id = {13337901},
  keywords = {ee, greendisc, greenlsi, josem},
  posted-at = {2014-10-03 18:42:16},
  priority = {2},
  series = {DAC'14},
  title = {Proactive and Reactive Thermal Aware Optimization Techniques to Minimize the Environmental Impact of Data Centers},
  year = {2014}
  }

• P. Arroba, J. L. Risco-Martín, M. Zapater, J. M. Moya, J. L. Ayala, and K. Olcoz, "Evolutionary power modeling for high-end servers in cloud data centers," in Mathematical modelling in engineering & human behaviour, 2014.
  [BibTeX]

  @inproceedings{ARZ+14,
  author = {Arroba, Patricia and Risco-Mart\'{\i}n, Jose L. and Zapater, Marina and Moya, Jose M. and Ayala, Jose L. and Olcoz, Katzalin},
  booktitle = {Mathematical Modelling in Engineering \& Human Behaviour},
  citeulike-article-id = {13337906},
  keywords = {cloud, ee, greendisc, greenlsi, josem},
  posted-at = {2014-10-03 18:41:51},
  priority = {2},
  title = {Evolutionary Power Modeling for High-end Servers in Cloud Data Centers},
  year = {2014}
  }

• M. Zapater, P. Arroba, J. L. Ayala, J. M. Moya, and K. Olcoz, "A novel energy-driven computing paradigm for e-health scenarios," Future generation computer systems, vol. 34, p. 138–154, 2014. doi:10.1016/j.future.2013.12.012
  [BibTeX] [Abstract] [Download PDF]
  

  A first-rate {e-Health} system saves lives, provides better patient care, allows complex but useful epidemiologic analysis and saves money. However, there may also be concerns about the costs and complexities associated with e-health implementation, and the need to solve issues about the energy footprint of the high-demanding computing facilities. This paper proposes a novel and evolved computing paradigm that: (i) provides the required computing and sensing resources; (ii) allows the population-wide diffusion; (iii) exploits the storage, communication and computing services provided by the Cloud; (iv) tackles the energy-optimization issue as a first-class requirement, taking it into account during the whole development cycle. The novel computing concept, and the multi-layer top-down energy-optimization methodology, obtain promising results in a realistic scenario for cardiovascular tracking and analysis, making the Home Assisted Living a reality.

  @article{ZAA+13,
  abstract = {A first-rate {e-Health} system saves lives, provides better patient care, allows complex but useful epidemiologic analysis and saves money. However, there may also be concerns about the costs and complexities associated with e-health implementation, and the need to solve issues about the energy footprint of the high-demanding computing facilities. This paper proposes a novel and evolved computing paradigm that: (i) provides the required computing and sensing resources; (ii) allows the population-wide diffusion; (iii) exploits the storage, communication and computing services provided by the Cloud; (iv) tackles the energy-optimization issue as a first-class requirement, taking it into account during the whole development cycle. The novel computing concept, and the multi-layer top-down energy-optimization methodology, obtain promising results in a realistic scenario for cardiovascular tracking and analysis, making the Home Assisted Living a reality.},
  author = {Zapater, Marina and Arroba, Patricia and Ayala, Jos\'{e} L. and Moya, Jos\'{e} M. and Olcoz, Katzalin},
  citeulike-article-id = {12882215},
  citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.future.2013.12.012},
  citeulike-linkout-1 = {http://www.sciencedirect.com/science/article/pii/S0167739X13002768},
  doi = {10.1016/j.future.2013.12.012},
  howpublished = {online},
  issn = {0167-739X},
  journal = {Future Generation Computer Systems},
  keywords = {ami, analysis, centers, cloud, computing, data, dc, efficiency, energy, green, greenlsi, it, josem, management, population, resource},
  month = may,
  pages = {138--154},
  posted-at = {2013-12-26 17:29:36},
  priority = {0},
  title = {A novel energy-driven computing paradigm for e-health scenarios},
  url = {http://www.sciencedirect.com/science/article/pii/S0167739X13002768},
  volume = {34},
  year = {2014}
  }

2013

• P. Malagón, J. M. Goyeneche, and J. M. Moya, "Exploiting parallelism opportunities in non-parallel architectures to improve NLFSR software implementations," in Xxviii conference on design of circuits and integrated systems, 2013, p. 454–460.
  [BibTeX] [Abstract]
  

  Linear and {Non-Linear} Feedback Shift Registers ({LFSR} and {NLFSR}) are widely used in the generation of pseudorandom sequences and as basic structures of block ciphers. The algorithms are structured in rounds where a new bit is calculated and shifted into the keystream or data word. They can be implemented as a set of binary operations over a set of bits belonging to a register and a bit-wise rotation performed in each round. Although these algorithms are more efficiently implemented in hardware, when run in software the binary operations are usually performed in an {ALU}, calculating only 1 bit at a time. But {ALUs} have the potential of performing more Boolean operations simultaneously. We propose to consider the {ALU} as a vector unit of Boolean {ALUs}. Therefore, we include a methodology to exploit the parallelization of the Boolean operations in the {ALU} when possible in order to improve the performance of software implementations. The optimization is susceptible to be incorporated and automatically applied by a compiler. Using {KeeLoq} as use case in a 16-bit platform we obtain an improvement factor in executed cycles of at least 2.45, increasing code size in bytes by at most 2.27.

  @inproceedings{MGM13,
  abstract = {Linear and {Non-Linear} Feedback Shift Registers ({LFSR} and {NLFSR}) are widely used in the generation of pseudorandom sequences and as basic structures of block ciphers. The algorithms are structured in rounds where a new bit is calculated and shifted into the keystream or data word. They can be implemented as a set of binary operations over a set of bits belonging to a register and a bit-wise rotation performed in each round. Although these algorithms are more efficiently implemented in hardware, when run in software the binary operations are usually performed in an {ALU}, calculating only 1 bit at a time. But {ALUs} have the potential of performing more Boolean operations simultaneously. We propose to consider the {ALU} as a vector unit of Boolean {ALUs}. Therefore, we include a methodology to exploit the parallelization of the Boolean operations in the {ALU} when possible in order to improve the performance of software implementations. The optimization is susceptible to be incorporated and automatically applied by a compiler. Using {KeeLoq} as use case in a 16-bit platform we obtain an improvement factor in executed cycles of at least 2.45, increasing code size in bytes by at most 2.27.},
  author = {Malag\'{o}n, P. and Goyeneche, J. M. and Moya, J. M.},
  booktitle = {XXVIII Conference on Design of Circuits and Integrated Systems},
  citeulike-article-id = {13581791},
  isbn = {978-84-8081-401-0},
  keywords = {bitslice, greenlsi, josem, nlfsr, sca},
  month = nov,
  pages = {454--460},
  posted-at = {2015-11-13 23:46:13},
  priority = {2},
  title = {Exploiting parallelism opportunities in non-parallel architectures to improve {NLFSR} software implementations},
  year = {2013}
  }

• J. Pagán, M. Zapater, Ó. Cubo, P. Arroba, V. Martín, and J. M. Moya, "A Cyber-Physical approach to combined HW-SW monitoring for improving energy efficiency in data centers," in Conference on design of circuits and integrated systems, 2013.
  [BibTeX] [Abstract]
  

  {High-Performance} Computing, Cloud computing and next-generation applications such {e-Health} or Smart Cities have dramatically increased the computational demand of Data Centers. The huge energy consumption, increasing levels of {CO2} and the economic costs of these facilities represent a challenge for industry and researchers alike. Recent research trends propose the usage of holistic optimization techniques to jointly minimize Data Center computational and cooling costs from a multilevel perspective. This paper presents an analysis on the parameters needed to integrate the Data Center in a holistic optimization framework and leverages the usage of {Cyber-Physical} systems to gather workload, server and environmental data via software techniques and by deploying a non-intrusive Wireless Sensor Network ({WSN}). This solution tackles data sampling, retrieval and storage from a reconfigurable perspective, reducing the amount of data generated for optimization by a 68\% without information loss, doubling the lifetime of the {WSN} nodes and allowing runtime energy minimization techniques in a real scenario.

  @inproceedings{PZC+13,
  abstract = {{High-Performance} Computing, Cloud computing and next-generation applications such {e-Health} or Smart Cities have dramatically increased the computational demand of Data Centers. The huge energy consumption, increasing levels of {CO2} and the economic costs of these facilities represent a challenge for industry and researchers alike. Recent research trends propose the usage of holistic optimization techniques to jointly minimize Data Center computational and cooling costs from a multilevel perspective. This paper presents an analysis on the parameters
  needed to integrate the Data Center in a holistic optimization framework and leverages the usage of {Cyber-Physical} systems to gather workload, server and environmental data via software techniques and by deploying a non-intrusive Wireless Sensor Network ({WSN}). This solution tackles data sampling, retrieval and storage from a reconfigurable perspective, reducing the amount of data generated for optimization by a 68\% without information loss, doubling the lifetime of the {WSN} nodes and allowing runtime energy minimization techniques in a real scenario.},
  author = {Pag\'{a}n, Josu\'{e} and Zapater, Marina and Cubo, \'{O}scar and Arroba, Patricia and Mart\'{\i}n, Vicente and Moya, Jos\'{e} M.},
  booktitle = {Conference on Design of Circuits and Integrated Systems},
  citeulike-article-id = {12651885},
  keywords = {cps, dc, greenlsi, josem, wsn},
  month = nov,
  posted-at = {2014-03-01 09:08:45},
  priority = {2},
  title = {A {Cyber-Physical} Approach to Combined {HW}-{SW} Monitoring for Improving Energy Efficiency in Data Centers},
  year = {2013}
  }

• P. Arroba, M. Zapater, J. L. Ayala, J. M. Moya, K. Olcoz, and R. Hermida, "On the Leakage-Power modeling for optimal server operation," in Jornadas sarteco, 2013.
  [BibTeX] [Abstract] [Download PDF]
  

  Leakage power consumption is a component of the total power consumption in data centers that is not traditionally considered in the set-point temperature of the room. However, the effect of this power component, increased with temperature, can determine the savings associated with the careful management of the cooling system, as well as the reliability of the system. The work presented in this paper detects the need of addressing leakage power in order to achieve substantial savings in the energy consumption of servers. In particular, our work shows that, by a careful detection and management of two working regions (low and high impact of thermal-dependent leakage), energy consumption of the datacenter can be optimized by a reduction of the cooling budget.

  @inproceedings{AZA+13,
  abstract = {Leakage power consumption is a component of the total power consumption in data centers that is not traditionally considered in the set-point temperature of the room. However, the effect of this power component, increased with temperature, can determine the savings associated with the careful management of the cooling system, as well as the reliability of the system. The work presented in this paper detects the need of addressing leakage power in order to achieve substantial savings in the energy
  consumption of servers. In particular, our work shows that, by a careful detection and management of two
  working regions (low and high impact of thermal-dependent leakage), energy consumption of the datacenter can be optimized by a reduction of the cooling
  budget.},
  author = {Arroba, Patricia and Zapater, Marina and Ayala, Jos\'{e} L. and Moya, Jos\'{e} M. and Olcoz, Katzalin and Hermida, Rom\'{a}n},
  booktitle = {Jornadas SARTECO},
  citeulike-article-id = {12651866},
  citeulike-linkout-0 = {http://www.sc.ehu.es/acwmialj/papers/2013\_jornadas.pdf},
  keywords = {greendisc, greenlsi, josem, modeling},
  month = sep,
  posted-at = {2014-03-01 09:08:13},
  priority = {2},
  title = {On the {Leakage-Power} Modeling for Optimal Server Operation},
  url = {http://www.sc.ehu.es/acwmialj/papers/2013\_jornadas.pdf},
  year = {2013}
  }

• Z. Bankovic, J. C. Vallejo, D. Fraga, and J. M. Moya, "Detecting false testimonies in reputation systems using self-organizing maps," Logic journal of the igpl, vol. 21, iss. 4, p. 549–559, 2013. doi:10.1093/jigpal/jzs028
  [BibTeX] [Abstract] [Download PDF]
  

  It has been demonstrated that rating trust and reputation of individual nodes is an effective approach in distributed environments in order to improve security, support decision-making and promote node collaboration. Nevertheless, these systems are vulnerable to deliberate false or unfair testimonies. In one scenario, the attackers collude to give negative feedback on the victim in order to lower or destroy its reputation. This attack is known as bad mouthing attack. In another scenario, a number of entities agree to give positive feedback on an entity (often with adversarial intentions). This attack is known as ballot stuffing. Both attack types can significantly deteriorate the performances of the network. The existing solutions for coping with these attacks are mainly concentrated on prevention techniques. In this work, we propose a solution that detects and isolates the abovementioned attackers, impeding them in this way to further spread their malicious activity. The approach is based on detecting outliers using clustering, in this case self-organizing maps. An important advantage of this approach is that we have no restrictions on training data, and thus there is no need for any data pre-processing. Testing results demonstrate the capability of the approach in detecting both bad mouthing and ballot stuffing attack in various scenarios.

  @article{BVFM13,
  abstract = {It has been demonstrated that rating trust and reputation of individual nodes is an effective approach in distributed environments in order to improve security, support decision-making and promote node collaboration. Nevertheless, these systems are vulnerable to deliberate false or unfair testimonies. In one scenario, the attackers collude to give negative feedback on the victim in order to lower or destroy its reputation. This attack is known as bad mouthing attack. In another scenario, a number of entities agree to give positive feedback on an entity (often with adversarial intentions). This attack is known as ballot stuffing. Both attack types can significantly deteriorate the performances of the network. The existing solutions for coping with these attacks are mainly concentrated on prevention techniques. In this work, we propose a solution that detects and isolates the abovementioned attackers, impeding them in this way to further spread their malicious activity. The approach is based on detecting outliers using clustering, in this case self-organizing maps. An important advantage of this approach is that we have no restrictions on training data, and thus there is no need for any data pre-processing. Testing results demonstrate the capability of the approach in detecting both bad mouthing and ballot stuffing attack in various scenarios.},
  author = {Bankovic, Zorana and Vallejo, Juan C. and Fraga, David and Moya, Jos\'{e} M.},
  citeulike-article-id = {12799817},
  citeulike-linkout-0 = {http://dx.doi.org/10.1093/jigpal/jzs028},
  doi = {10.1093/jigpal/jzs028},
  journal = {Logic Journal of the IGPL},
  keywords = {ami, greenlsi, josem, repsys},
  number = {4},
  pages = {549--559},
  posted-at = {2013-11-25 08:51:40},
  priority = {0},
  title = {Detecting false testimonies in reputation systems using self-organizing maps},
  url = {http://dx.doi.org/10.1093/jigpal/jzs028},
  volume = {21},
  year = {2013}
  }

• M. Zapater, J. L. Ayala, J. M. Moya, K. Vaidyanathan, K. Gross, and A. K. Coskun, "Leakage and temperature aware server control for improving energy efficiency in data centers," in Proceedings of the conference on design, automation and test in europe, 2013, p. 266–269.
  [BibTeX] [Abstract] [Download PDF]
  

  Reducing the energy consumption for computation and cooling in servers is a major challenge considering the data center energy costs today. To ensure energy-efficient operation of servers in data centers, the relationship among computational power, temperature, leakage, and cooling power needs to be analyzed. By means of an innovative setup that enables monitoring and controlling the computing and cooling power consumption separately on a commercial enterprise server, this paper studies temperature-leakage-energy tradeoffs, obtaining an empirical model for the leakage component. Using this model, we design a controller that continuously seeks and settles at the optimal fan speed to minimize the energy consumption for a given workload. We run a customized dynamic load-synthesis tool to stress the system. Our proposed cooling controller achieves up to 9\% energy savings and {30W} reduction in peak power in comparison to the default cooling control scheme.

  @inproceedings{ZAM+13,
  abstract = {Reducing the energy consumption for computation and cooling in servers is a major challenge considering the data center energy costs today. To ensure energy-efficient operation of servers in data centers, the relationship among computational power, temperature, leakage, and cooling power needs to be analyzed. By means of an innovative setup that enables
  monitoring and controlling the computing and cooling power consumption separately on a commercial enterprise server, this paper studies temperature-leakage-energy tradeoffs, obtaining an empirical model for the leakage component. Using this model, we design a controller that continuously seeks and settles at the
  optimal fan speed to minimize the energy consumption for a given workload. We run a customized dynamic load-synthesis tool to stress the system. Our proposed cooling controller achieves up to 9\% energy savings and {30W} reduction in peak power in comparison to the default cooling control scheme.},
  author = {Zapater, Marina and Ayala, Jos\'{e} L. and Moya, Jos\'{e} M. and Vaidyanathan, Kalyan and Gross, Kenny and Coskun, Ayse K.},
  booktitle = {Proceedings of the Conference on Design, Automation and Test in Europe},
  citeulike-article-id = {12231242},
  citeulike-linkout-0 = {http://dl.acm.org/citation.cfm?id=2485354},
  isbn = {978-1-4503-2153-2},
  keywords = {cooling, dc, greenlsi, josem},
  pages = {266--269},
  posted-at = {2013-04-06 08:39:15},
  priority = {2},
  series = {DATE '13},
  title = {Leakage and Temperature Aware Server Control for Improving Energy Efficiency in Data Centers},
  url = {http://dl.acm.org/citation.cfm?id=2485354},
  year = {2013}
  }

• Z. Banković, D. Fraga, J. M. Moya, J. C. Vallejo, P. Malagón, Á. Araujo, J. de Goyeneche, E. Romero, J. Blesa, D. Villanueva, and O. Nieto-Taladriz, "Bio-inspired enhancement of reputation systems for intelligent environments," Information sciences, vol. 222, p. 99–112, 2013. doi:10.1016/j.ins.2011.07.032
  [BibTeX] [Abstract] [Download PDF]
  

  Providing security to the emerging field of ambient intelligence will be difficult if we rely only on existing techniques, given their dynamic and heterogeneous nature. Moreover, security demands of these systems are expected to grow, as many applications will require accurate context modeling. In this work we propose an enhancement to the reputation systems traditionally deployed for securing these systems. Different anomaly detectors are combined using the immunological paradigm to optimize reputation system performance in response to evolving security requirements. As an example, the experiments show how a combination of detectors based on unsupervised techniques (self-organizing maps and genetic algorithms) can help to significantly reduce the global response time of the reputation system. The proposed solution offers many benefits: scalability, fast response to adversarial activities, ability to detect unknown attacks, high adaptability, and high ability in detecting and confining attacks. For these reasons, we believe that our solution is capable of coping with the dynamism of ambient intelligence systems and the growing requirements of security demands.

  @article{BFM+13,
  abstract = {Providing security to the emerging field of ambient intelligence will be difficult if we rely only on existing techniques, given their dynamic and heterogeneous nature. Moreover, security demands of these systems are expected to grow, as many applications will require accurate context modeling. In this work we propose an enhancement to the reputation systems traditionally deployed for securing these systems. Different anomaly detectors are combined using the immunological paradigm to optimize reputation system performance in response to evolving security requirements. As an example, the experiments show how a combination of detectors based on unsupervised techniques (self-organizing maps and genetic algorithms) can help to significantly reduce the global response time of the reputation system. The proposed solution offers many benefits: scalability, fast response to adversarial activities, ability to detect unknown attacks, high adaptability, and high ability in detecting and confining attacks. For these reasons, we believe that our solution is capable of coping with the dynamism of ambient intelligence systems and the growing requirements of security demands.},
  author = {Bankovi\'{c}, Zorana and Fraga, David and Moya, Jos\'{e} M. and Vallejo, Juan C. and Malag\'{o}n, Pedro and Araujo, \'{A}lvaro and de Goyeneche, Juan-Mariano and Romero, Elena and Blesa, Javier and Villanueva, Daniel and Nieto-Taladriz, Octavio},
  citeulike-article-id = {9654296},
  citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.ins.2011.07.032},
  doi = {10.1016/j.ins.2011.07.032},
  issn = {00200255},
  journal = {Information Sciences},
  keywords = {greenlsi, josem},
  month = feb,
  pages = {99--112},
  posted-at = {2012-11-18 18:39:33},
  priority = {2},
  publisher = {Elsevier},
  title = {Bio-inspired enhancement of reputation systems for intelligent environments},
  url = {http://dx.doi.org/10.1016/j.ins.2011.07.032},
  volume = {222},
  year = {2013}
  }

2012

• Z. Banković, D. Fraga, J. Vallejo, and J. Moya, "Self-Organizing maps versus growing neural gas in detecting data outliers for security applications," in Hybrid artificial intelligent systems, E. Corchado, V. Snášel, A. Abraham, M. Woźniak, M. Graña, and S. Cho, Eds., Springer Berlin Heidelberg, 2012, vol. 7209, p. 89–96. doi:10.1007/978-3-642-28931-6_9
  [BibTeX] [Abstract] [Download PDF]
  

  Our previous work has demonstrated that clustering-based outlier detection approach offers numerous advantages for detecting attacks in Wireless Sensor Networks, above all adaptability and the possibility to detect unknown attacks. In this work we provide a comparison of Self-organizing maps ({SOM}) and Growing Neural Gas ({GNG}) used for this purpose. Our results reveal that {GNG} is superior to {SOM} when it comes to the level of presence of anomalous data during the training, as {GNG} is capable of detecting the attack even with small portion of normal data during the training, while {SOM} need the majority of the training data to be normal in order to detect it. On the other hand, after both being trained with normal data, {SOM} performs somewhat better as the attack becomes more aggressive, i.e. it exhibits higher detection rate, although both are capable of detecting the attack in each case.

  @incollection{BFVM12,
  abstract = {Our previous work has demonstrated that clustering-based outlier detection approach offers numerous advantages for detecting attacks in Wireless Sensor Networks, above all adaptability and the possibility to detect unknown attacks. In this work we provide a comparison of Self-organizing maps ({SOM}) and Growing Neural Gas ({GNG}) used for this purpose. Our results reveal that {GNG} is superior to {SOM} when it comes to the level of presence of anomalous data during the training, as {GNG} is capable of detecting the attack even with small portion of normal data during the training, while {SOM} need the majority of the training data to be normal in order to detect it. On the other hand, after both being trained with normal data, {SOM} performs somewhat better as the attack becomes more aggressive, i.e. it exhibits higher detection rate, although both are capable of detecting the attack in each case.},
  author = {Bankovi\'{c}, Zorana and Fraga, David and Vallejo, JuanCarlos and Moya, Jos\'{e}M},
  booktitle = {Hybrid Artificial Intelligent Systems},
  citeulike-article-id = {13942918},
  citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-642-28931-6\_9},
  citeulike-linkout-1 = {http://link.springer.com/chapter/10.1007/978-3-642-28931-6\_9},
  doi = {10.1007/978-3-642-28931-6\_9},
  editor = {Corchado, Emilio and Sn\'{a}\v{s}el, V\'{a}clav and Abraham, Ajith and Wo\'{z}niak, Micha{\l} and Gra\~{n}a, Manuel and Cho, Sung-Bae},
  keywords = {dfraga, greenlsi, josem, repsys, security},
  pages = {89--96},
  posted-at = {2016-02-27 12:03:06},
  priority = {2},
  publisher = {Springer Berlin Heidelberg},
  series = {Lecture Notes in Computer Science},
  title = {{Self-Organizing} Maps versus Growing Neural Gas in Detecting Data Outliers for Security Applications},
  url = {http://dx.doi.org/10.1007/978-3-642-28931-6\_9},
  volume = {7209},
  year = {2012}
  }

• D. Fraga, Z. Bankovic, and J. M. Moya, "A taxonomy of trust and reputation system attacks," in Trust, security and privacy in computing and communications (trustcom), 2012 ieee 11th international conference on, 2012, p. 41–50. doi:10.1109/trustcom.2012.58
  [BibTeX] [Abstract] [Download PDF]
  

  Trust and reputation have been suggested as an effective security mechanism for open and distributed environments. However, even though there exists a high number of identified attacks against Trust and Reputation Systems ({TRS}), a generic security framework to identify all of them in a holistic way has not yet been proposed. This work presents a {TRS} attack taxonomy based on an {TRS} architectural model and a set of well-known security topics. Based on this taxonomy, two main deficiencies of the state-of-the-art in {TRS} security literature are detected: the existence of {TRS} attacks that have received few attention from the {TRS} community despite its importance, and potential threats that have not been previously identified. Finally, a real-life {TRS} scenario is analyzed as a proof-of-concept of the proposed taxonomy.

  @inproceedings{FBM12,
  abstract = {Trust and reputation have been suggested as an effective security mechanism for open and distributed environments. However, even though there exists a high number of identified attacks against Trust and Reputation Systems ({TRS}), a generic security framework to identify all of them in a holistic way has not yet been proposed. This work presents a {TRS} attack taxonomy based on an {TRS} architectural model and a set of well-known security topics. Based on this taxonomy, two main deficiencies of the state-of-the-art in {TRS} security literature are detected: the existence of {TRS} attacks that have received few attention from the {TRS} community despite its importance, and potential threats that have not been previously identified. Finally, a real-life {TRS} scenario is analyzed as a proof-of-concept of the proposed taxonomy.},
  author = {Fraga, D. and Bankovic, Z. and Moya, J. M.},
  booktitle = {Trust, Security and Privacy in Computing and Communications (TrustCom), 2012 IEEE 11th International Conference on},
  citeulike-article-id = {13942896},
  citeulike-linkout-0 = {http://dx.doi.org/10.1109/trustcom.2012.58},
  citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=6295956},
  doi = {10.1109/trustcom.2012.58},
  institution = {Dept. Of Electr. Eng. ETSI Telecomun., Univ. Politec. de Madrid, Madrid, Spain},
  isbn = {978-1-4673-2172-3},
  keywords = {dfraga, greenlsi, josem, repsys, security},
  month = jun,
  pages = {41--50},
  posted-at = {2016-02-27 11:34:19},
  priority = {2},
  publisher = {IEEE},
  title = {A Taxonomy of Trust and Reputation System Attacks},
  url = {http://dx.doi.org/10.1109/trustcom.2012.58},
  year = {2012}
  }

• M. Zapater, J. L. Ayala, and J. M. Moya, "GreenDisc: a HW/SW energy optimization framework in globally distributed computation," in Ubiquitous computing and ambient intelligence, J. Bravo, D. López-de Ipiña, and F. Moya, Eds., Springer Berlin Heidelberg, 2012, p. 1–8. doi:10.1007/978-3-642-35377-2_1
  [BibTeX] [Abstract] [Download PDF]
  

  In recent future, wireless sensor networks ({WSNs}) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of {WSNs} facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers ({DCs}). The high economical and environmental impact of the energy consumption in {DCs} requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed. In this context, this paper shows the following on-going research lines and obtained results. In the field of {WSNs}: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of {DCs}: energy-optimal workload assignment policies in heterogeneous {DCs}, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the {DCs} that process the data provided by the {WSNs}.

  @incollection{ZAM12b,
  abstract = {In recent future, wireless sensor networks ({WSNs}) will experience a broad high-scale deployment (millions of nodes in the national area) with multiple information sources per node, and with very specific requirements for signal processing. In parallel, the broad range deployment of {WSNs} facilitates the definition and execution of ambitious studies, with a large input data set and high computational complexity. These computation resources, very often heterogeneous and driven on-demand, can only be satisfied by high-performance Data Centers ({DCs}). The high economical and environmental impact of the energy consumption in {DCs} requires aggressive energy optimization policies. These policies have been already detected but not successfully proposed.
  In this context, this paper shows the following on-going research lines and obtained results. In the field of {WSNs}: energy optimization in the processing nodes from different abstraction levels, including reconfigurable application specific architectures, efficient customization of the memory hierarchy, energy-aware management of the wireless interface, and design automation for signal processing applications. In the field of {DCs}: energy-optimal workload assignment policies in heterogeneous {DCs}, resource management policies with energy consciousness, and efficient cooling mechanisms that will cooperate in the minimization of the electricity bill of the {DCs} that process the data provided by the {WSNs}.},
  author = {Zapater, Marina and Ayala, Jos\'{e} L. and Moya, Jose M.},
  booktitle = {Ubiquitous Computing and Ambient Intelligence},
  citeulike-article-id = {11824300},
  citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-642-35377-2\_1},
  doi = {10.1007/978-3-642-35377-2\_1},
  editor = {Bravo, Jos\'{e} and L\'{o}pez-de Ipi\~{n}a, Diego and Moya, Francisco},
  keywords = {ami, greenlsi, josem},
  pages = {1--8},
  posted-at = {2012-12-04 09:00:30},
  priority = {2},
  publisher = {Springer Berlin Heidelberg},
  series = {Lecture Notes in Computer Science},
  title = {{GreenDisc}: A {HW}/{SW} Energy Optimization Framework in Globally Distributed Computation},
  url = {http://dx.doi.org/10.1007/978-3-642-35377-2\_1},
  year = {2012}
  }

• M. Zapater, J. L. Ayala, and J. M. Moya, "Leveraging heterogeneity for energy minimization in data centers," in Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID 2012), Washington, DC, USA, 2012. doi:10.1109/CCGrid.2012.34
  [BibTeX] [Abstract] [Download PDF]
  

  Energy consumption in data centers is nowadays a critical objective because of its dramatic environmental and economic impact. Over the last years, several approaches have been proposed to tackle the energy/cost optimization problem, but most of them have failed on providing an analytical model to target both the static and dynamic optimization domains for complex heterogeneous data centers. This paper proposes and solves an optimization problem for the energy-driven configuration of a heterogeneous data center. It also advances in the proposition of a new mechanism for task allocation and distribution of workload. The combination of both approaches outperforms previous published results in the field of energy minimization in heterogeneous data centers and scopes a promising area of research.

  @inproceedings{ZAM12,
  abstract = {Energy consumption in data centers is nowadays a critical objective because of its dramatic environmental and economic impact. Over the last years, several approaches have been proposed to tackle the energy/cost optimization problem, but most of them have failed on providing an analytical model to target both the static and dynamic optimization domains for complex heterogeneous data centers. This paper proposes and solves an optimization problem for the energy-driven configuration of a heterogeneous data center. It also advances in the proposition of a new mechanism for task allocation and distribution of workload. The combination of both approaches outperforms previous published results in the field of energy minimization in heterogeneous data centers and scopes a promising area of research.},
  address = {Washington, DC, USA},
  author = {Zapater, Marina and Ayala, Jose L. and Moya, Jose M.},
  booktitle = {{Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID 2012)}},
  citeulike-article-id = {11736953},
  citeulike-linkout-0 = {http://dx.doi.org/10.1109/CCGrid.2012.34},
  doi = {10.1109/CCGrid.2012.34},
  keywords = {centers, computing, data, energy-aware, green, greenlsi, heterogeneous, josem, optimization},
  posted-at = {2012-11-21 00:02:39},
  priority = {0},
  publisher = {IEEE Computer Society},
  series = {CCGRID '12},
  title = {Leveraging Heterogeneity for Energy Minimization in Data Centers},
  url = {http://dx.doi.org/10.1109/CCGrid.2012.34},
  year = {2012}
  }

• Z. Banković, D. Fraga, J. M. Moya, and J. C. Vallejo, "Detecting unknown attacks in wireless sensor networks that contain mobile nodes," Sensors, vol. 12, iss. 8, p. 10834–10850, 2012. doi:10.3390/s120810834
  [BibTeX] [Abstract] [Download PDF]
  

  As wireless sensor networks are usually deployed in unattended areas, security policies cannot be updated in a timely fashion upon identification of new attacks. This gives enough time for attackers to cause significant damage. Thus, it is of great importance to provide protection from unknown attacks. However, existing solutions are mostly concentrated on known attacks. On the other hand, mobility can make the sensor network more resilient to failures, reactive to events, and able to support disparate missions with a common set of sensors, yet the problem of security becomes more complicated. In order to address the issue of security in networks with mobile nodes, we propose a machine learning solution for anomaly detection along with the feature extraction process that tries to detect temporal and spatial inconsistencies in the sequences of sensed values and the routing paths used to forward these values to the base station. We also propose a special way to treat mobile nodes, which is the main novelty of this work. The data produced in the presence of an attacker are treated as outliers, and detected using clustering techniques. These techniques are further coupled with a reputation system, in this way isolating compromised nodes in timely fashion. The proposal exhibits good performances at detecting and confining previously unseen attacks, including the cases when mobile nodes are compromised.

  @article{BFM+12,
  abstract = {As wireless sensor networks are usually deployed in unattended areas, security policies cannot be updated in a timely fashion upon identification of new attacks. This gives enough time for attackers to cause significant damage. Thus, it is of great importance to provide protection from unknown attacks. However, existing solutions are mostly concentrated on known attacks. On the other hand, mobility can make the sensor network more resilient to failures, reactive to events, and able to support disparate missions with a common set of sensors, yet the problem of security becomes more complicated. In order to address the issue of security in networks with mobile nodes, we propose a machine learning solution for anomaly detection along with the feature extraction process that tries to detect temporal and spatial inconsistencies in the sequences of sensed values and the routing paths used to forward these values to the base station. We also propose a special way to treat mobile nodes, which is the main novelty of this work. The data produced in the presence of an attacker are treated as outliers, and detected using clustering techniques. These techniques are further coupled with a reputation system, in this way isolating compromised nodes in timely fashion. The proposal exhibits good performances at detecting and confining previously unseen attacks, including the cases when mobile nodes are compromised.},
  author = {Bankovi\'{c}, Zorana and Fraga, David and Moya, Jos\'{e} M. and Vallejo, Juan C.},
  citeulike-article-id = {11095233},
  citeulike-linkout-0 = {http://dx.doi.org/10.3390/s120810834},
  day = {07},
  doi = {10.3390/s120810834},
  issn = {1424-8220},
  journal = {Sensors},
  keywords = {greenlsi, josem},
  month = aug,
  number = {8},
  pages = {10834--10850},
  posted-at = {2012-11-18 18:39:40},
  priority = {2},
  title = {Detecting Unknown Attacks in Wireless Sensor Networks That Contain Mobile Nodes},
  url = {http://dx.doi.org/10.3390/s120810834},
  volume = {12},
  year = {2012}
  }

• M. Zapater, C. Sanchez, J. L. Ayala, J. M. Moya, and J. L. Risco-Martín, "Ubiquitous green computing techniques for high demand applications in smart environments," Sensors, vol. 12, iss. 8, p. 10659–10677, 2012. doi:10.3390/s120810659
  [BibTeX] [Abstract] [Download PDF]
  

  Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in {WSNs} infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the {WSN} infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time.

  @article{ZSA+12,
  abstract = {Ubiquitous sensor network deployments, such as the ones found in Smart cities and Ambient intelligence applications, require constantly increasing high computational demands in order to process data and offer services to users. The nature of these applications imply the usage of data centers. Research has paid much attention to the energy consumption of the sensor nodes in {WSNs} infrastructures. However, supercomputing facilities are the ones presenting a higher economic and environmental impact due to their very high power consumption. The latter problem, however, has been disregarded in the field of smart environment services. This paper proposes an energy-minimization workload assignment technique, based on heterogeneity and application-awareness, that redistributes low-demand computational tasks from high-performance facilities to idle nodes with low and medium resources in the {WSN} infrastructure. These non-optimal allocation policies reduce the energy consumed by the whole infrastructure and the total execution time.},
  author = {Zapater, Marina and Sanchez, Cesar and Ayala, Jose L. and Moya, Jose M. and Risco-Mart\'{\i}n, Jos\'{e} L.},
  citeulike-article-id = {11021307},
  citeulike-linkout-0 = {http://dx.doi.org/10.3390/s120810659},
  day = {03},
  doi = {10.3390/s120810659},
  issn = {1424-8220},
  journal = {Sensors},
  keywords = {greenlsi, josem},
  month = aug,
  number = {8},
  pages = {10659--10677},
  posted-at = {2012-11-18 18:39:26},
  priority = {2},
  title = {Ubiquitous Green Computing Techniques for High Demand Applications in Smart Environments},
  url = {http://dx.doi.org/10.3390/s120810659},
  volume = {12},
  year = {2012}
  }

• P. Malagón, J. de Goyeneche, M. Zapater, J. M. Moya, and Z. Banković, "Compiler optimizations as a countermeasure against Side-Channel analysis in MSP430-based devices," Sensors, vol. 12, iss. 6, p. 7994–8012, 2012. doi:10.3390/s120607994
  [BibTeX] [Abstract] [Download PDF]
  

  Ambient Intelligence ({AmI}) requires devices everywhere, dynamic and massively distributed networks of low-cost nodes that, among other data, manage private information or control restricted operations. {MSP430}, a 16-bit microcontroller, is used in {WSN} platforms, as the {TelosB}. Physical access to devices cannot be restricted, so attackers consider them a target of their malicious attacks in order to obtain access to the network. Side-channel analysis ({SCA}) easily exploits leakages from the execution of encryption algorithms that are dependent on critical data to guess the key value. In this paper we present an evaluation framework that facilitates the analysis of the effects of compiler and backend optimizations on the resistance against statistical {SCA}. We propose an optimization-based software countermeasure that can be used in current low-cost devices to radically increase resistance against statistical {SCA}, analyzed with the new framework.

  @article{MGZ+12,
  abstract = {Ambient Intelligence ({AmI}) requires devices everywhere, dynamic and massively distributed networks of low-cost nodes that, among other data, manage private information or control restricted operations. {MSP430}, a 16-bit microcontroller, is used in {WSN} platforms, as the {TelosB}. Physical access to devices cannot be restricted, so attackers consider them a target of their malicious attacks in order to obtain access to the network. Side-channel analysis ({SCA}) easily exploits leakages from the execution of encryption algorithms that are dependent on critical data to guess the key value. In this paper we present an evaluation framework that facilitates the analysis of the effects of compiler and backend optimizations on the resistance against statistical {SCA}. We propose an optimization-based software countermeasure that can be used in current low-cost devices to radically increase resistance against statistical {SCA}, analyzed with the new framework.},
  author = {Malag\'{o}n, Pedro and de Goyeneche, Juan-Mariano and Zapater, Marina and Moya, Jos\'{e} M. and Bankovi\'{c}, Zorana},
  citeulike-article-id = {10853003},
  citeulike-linkout-0 = {http://dx.doi.org/10.3390/s120607994},
  day = {08},
  doi = {10.3390/s120607994},
  issn = {1424-8220},
  journal = {Sensors},
  keywords = {greenlsi, josem},
  month = jun,
  number = {6},
  pages = {7994--8012},
  posted-at = {2012-11-18 18:39:16},
  priority = {2},
  title = {Compiler Optimizations as a Countermeasure against {Side-Channel} Analysis in {MSP430}-Based Devices},
  url = {http://dx.doi.org/10.3390/s120607994},
  volume = {12},
  year = {2012}
  }

2011

• Z. Bankovic, D. Fraga, J. C. Vallejo, and J. M. Moya, "Improving reputation systems for wireless sensor networks using genetic algorithms," in Proceedings of the 13th annual conference on genetic and evolutionary computation, New York, NY, USA, 2011, p. 1643–1650. doi:10.1145/2001576.2001798
  [BibTeX] [Abstract] [Download PDF]
  

  In this article we propose to couple reputation systems for wireless sensor networks with a genetic algorithm in order to improve their time of response to adversarial activities. The reputation of each node is assigned by an unsupervised genetic algorithm trained for detecting outliers in the data. The response of the system consists in assigning low reputation values to the compromised nodes cutting them off from the rest of the network. The genetic algorithm uses the feature extraction process that does not capture the properties of the attacks, but rather relies on the existing temporal and spatial redundancy in sensor networks and tries to detect temporal and spatial inconsistencies in the sequences of sensed values and the routing paths used to forward these values to the base station. This solution offers many benefits: scalable solution, fast response to thwart activities, ability to detect unknown attacks, high adaptability, and high ability in detecting and confining attacks. Comparing to the standard clustering algorithms, the benefit of this one is that it is not necessary to assign the number of clusters from the beginning. The solution is also robust to both parameter changes and the presence of large amounts of malicious data in the training and testing datasets.

  @inproceedings{BFVM11,
  abstract = {In this article we propose to couple reputation systems for wireless sensor networks with a genetic algorithm in order to improve their time of response to adversarial activities. The reputation of each node is assigned by an unsupervised genetic algorithm trained for detecting outliers in the data. The response of the system consists in assigning low reputation values to the compromised nodes cutting them off from the rest of the network. The genetic algorithm uses the feature extraction process that does not capture the properties of the attacks, but rather relies on the existing temporal and spatial redundancy in sensor networks and tries to detect temporal and spatial inconsistencies in the sequences of sensed values and the routing paths used to forward these values to the base station. This solution offers many benefits: scalable solution, fast response to thwart activities, ability to detect unknown attacks, high adaptability, and high ability in detecting and confining attacks. Comparing to the standard clustering algorithms, the benefit of this one is that it is not necessary to assign the number of clusters from the beginning. The solution is also robust to both parameter changes and the presence of large amounts of malicious data in the training and testing datasets.},
  address = {New York, NY, USA},
  author = {Bankovic, Zorana and Fraga, David and Vallejo, Juan C. and Moya, Jos{\'{e}} M.},
  booktitle = {Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation},
  citeulike-article-id = {13942917},
  citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=2001576.2001798},
  citeulike-linkout-1 = {http://dx.doi.org/10.1145/2001576.2001798},
  doi = {10.1145/2001576.2001798},
  isbn = {978-1-4503-0557-0},
  keywords = {dfraga, greenlsi, josem, repsys},
  location = {Dublin, Ireland},
  pages = {1643--1650},
  posted-at = {2016-02-27 11:59:03},
  priority = {2},
  publisher = {ACM},
  series = {GECCO '11},
  title = {Improving Reputation Systems for Wireless Sensor Networks Using Genetic Algorithms},
  url = {http://dx.doi.org/10.1145/2001576.2001798},
  year = {2011}
  }

• Z. Bankovic, J. M. Moya, J. C. Vallejo, D. Fraga, and P. Malagon, "Holistic solution for confining insider attacks in wireless sensor networks using reputation systems coupled with clustering techniques," in Trust, security and privacy in computing and communications (trustcom), 2011 ieee 10th international conference on, 2011, p. 61–72. doi:10.1109/trustcom.2011.12
  [BibTeX] [Abstract] [Download PDF]
  

  The most serious obstacle in further proliferation of wireless sensor networks is their low level of security, where the insider attacks are the most challenging issue. In this work we propose a holistic solution for detecting and confining insider attacks that couples reputation systems with clustering techniques, namely unsupervised genetic algorithm and self-organizing maps, trained for detecting outliers in data. The novelty of this work is the redundancy in detecting agents, their evaluation based on the majority voting and the calculation of the reputation as the average value, which makes it more robust to different attack scenarios and their parameter variations. The algorithms use the feature space based on sequences of sensor outputs (both temporal and spatial), as well as the routing paths used to forward the data to the base station, and designed with the idea of introducing the ability to detect a wide range of attacks. The solution performs both attack detection and recovery from attacks, and it offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability and high ability in detecting and confining attacks.

  @inproceedings{BMV+11,
  abstract = {The most serious obstacle in further proliferation of wireless sensor networks is their low level of security, where the insider attacks are the most challenging issue. In this work we propose a holistic solution for detecting and confining insider attacks that couples reputation systems with clustering techniques, namely unsupervised genetic algorithm and self-organizing maps, trained for detecting outliers in data. The novelty of this work is the redundancy in detecting agents, their evaluation based on the majority voting and the calculation of the reputation as the average value, which makes it more robust to different attack scenarios and their parameter variations. The algorithms use the feature space based on sequences of sensor outputs (both temporal and spatial), as well as the routing paths used to forward the data to the base station, and designed with the idea of introducing the ability to detect a wide range of attacks. The solution performs both attack detection and recovery from attacks, and it offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability and high ability in detecting and confining attacks.},
  author = {Bankovic, Z. and Moya, J. M. and Vallejo, J. C. and Fraga, D. and Malagon, P.},
  booktitle = {Trust, Security and Privacy in Computing and Communications (TrustCom), 2011 IEEE 10th International Conference on},
  citeulike-article-id = {13942902},
  citeulike-linkout-0 = {http://dx.doi.org/10.1109/trustcom.2011.12},
  citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=6120804},
  doi = {10.1109/trustcom.2011.12},
  institution = {Dept. Of Electr. Eng. ETSI Telecomun., Univ. Politec. de Madrid, Madrid, Spain},
  isbn = {978-1-4577-2135-9},
  keywords = {dfraga, greenlsi, josem, repsys, security},
  month = nov,
  pages = {61--72},
  posted-at = {2016-02-27 11:36:31},
  priority = {2},
  publisher = {IEEE},
  title = {Holistic Solution for Confining Insider Attacks in Wireless Sensor Networks Using Reputation Systems Coupled with Clustering Techniques},
  url = {http://dx.doi.org/10.1109/trustcom.2011.12},
  year = {2011}
  }

• D. Fraga, Á. Gutiérrez, J. C. Vallejo, A. Campo, and Z. Bankovic, "Improving social odometry robot networks with distributed reputation systems for collaborative purposes," Sensors, vol. 11, iss. 12, p. 11372–11389, 2011. doi:10.3390/s111211372
  [BibTeX] [Abstract] [Download PDF]
  

  The improvement of odometry systems in collaborative robotics remains an important challenge for several applications. Social odometry is a social technique which confers the robots the possibility to learn from the others. This paper analyzes social odometry and proposes and follows a methodology to improve its behavior based on cooperative reputation systems. We also provide a reference implementation that allows us to compare the performance of the proposed solution in highly dynamic environments with the performance of standard social odometry techniques. Simulation results quantitatively show the benefits of this collaborative approach that allows us to achieve better performances than social odometry.

  @article{FGV+11,
  abstract = {The improvement of odometry systems in collaborative robotics remains an important challenge for several applications. Social odometry is a social technique which confers the robots the possibility to learn from the others. This paper analyzes social odometry and proposes and follows a methodology to improve its behavior based on cooperative reputation systems. We also provide a reference implementation that allows us to compare the performance of the proposed solution in highly dynamic environments with the performance of standard social odometry techniques. Simulation results quantitatively show the benefits of this collaborative approach that allows us to achieve better performances than social odometry.},
  author = {Fraga, David and Guti\'{e}rrez, \'{A}lvaro and Vallejo, Juan C. and Campo, Alexandre and Bankovic, Zorana},
  citeulike-article-id = {10087787},
  citeulike-linkout-0 = {http://dx.doi.org/10.3390/s111211372},
  day = {30},
  doi = {10.3390/s111211372},
  issn = {1424-8220},
  journal = {Sensors},
  keywords = {dfraga, greenlsi, repsys, security},
  month = nov,
  number = {12},
  pages = {11372--11389},
  posted-at = {2016-02-27 11:24:33},
  priority = {2},
  title = {Improving Social Odometry Robot Networks with Distributed Reputation Systems for Collaborative Purposes},
  url = {http://dx.doi.org/10.3390/s111211372},
  volume = {11},
  year = {2011}
  }

• M. Zapater, P. Arroba, J. M. Moya, and Z. Banković, "A State-of-the-Art on energy efficiency in today's datacentres: researcher's contributions and practical approaches," Upgrade, vol. 12, iss. 4, p. 67–74, 2011.
  [BibTeX] [Abstract] [Download PDF]
  

  Energy efficiency has become an issue of great importance in today's datacentres. Metrics like Top500, which measure speed and performance, are beginning to lose importance in favor of others such as Green500. In order to increase energy efficiency of datacentres and save energy costs, the research community proposes solutions from both the computing and the cooling point of view, while European and {US} Institutions publish best practice manuals on energy-efficiency for datacentre owners. However, even though best practices are beginning to be implemented, most of the solutions offered by researchers are not yet used in real production environments. This paper makes a survey of the solutions proposed by researchers as well as the practices that real datacentres apply in order to increase the energy-efficiency of their facilities, and to find the reasons that create this gap between research and innovation in datacentres.

  @article{ZAM+2011,
  abstract = {Energy efficiency has become an issue of great importance in today's datacentres. Metrics like Top500, which measure speed and performance, are beginning to lose importance in favor of others such as Green500. In order to increase energy efficiency of datacentres and save energy costs, the research community proposes solutions from both the computing and the cooling point of view, while European and {US} Institutions publish best practice manuals on energy-efficiency for datacentre owners. However, even though best practices are beginning to be implemented, most of the solutions offered by researchers are not yet used in real production environments. This paper makes a survey of the solutions proposed by researchers as well as the practices that real datacentres apply in order to increase the energy-efficiency of their facilities, and to find the reasons that create this gap between research and innovation in datacentres.},
  author = {Zapater, Marina and Arroba, Patricia and Moya, Jos\'{e} M. and Bankovi\'{c}, Zorana},
  citeulike-article-id = {11737365},
  citeulike-linkout-0 = {http://www.cepis.org/upgrade/media/zapater\_2011\_41.pdf},
  issn = {1684-5285},
  journal = {UPGRADE},
  keywords = {datacenters, dc, efficiency, energy, greenlsi, josem, state-of-art},
  number = {4},
  pages = {67--74},
  posted-at = {2014-03-01 08:51:04},
  priority = {2},
  publisher = {CEPIS},
  title = {A {State-of-the-Art} on Energy Efficiency in Today's Datacentres: Researcher's Contributions and Practical Approaches},
  url = {http://www.cepis.org/upgrade/media/zapater\_2011\_41.pdf},
  volume = {12},
  year = {2011}
  }

• M. Zapater, J. de Goyeneche, J. M. Moya, P. Malagón, and Z. Bankovic, "Thermal-Aware optimization of heterogeneous systems," in 26th Conference on Design of Circuits and Integrated Systems, 2011.
  [BibTeX]

  @inproceedings{ZGM+11,
  author = {Zapater, Marina and de Goyeneche, Juan-Mariano and Moya, Jos\'{e} M. and Malag\'{o}n, Pedro and Bankovic, Zorana},
  booktitle = {{26th Conference on Design of Circuits and Integrated Systems}},
  citeulike-article-id = {11737371},
  keywords = {datacenters, greenlsi, heterogeneous, josem},
  month = nov,
  posted-at = {2012-11-22 15:29:29},
  priority = {2},
  title = {{Thermal-Aware} Optimization of Heterogeneous Systems},
  year = {2011}
  }

• Z. Bankovic, D. Fraga, J. M. Moya, J. C. Vallejo, P. Malagón, Á. Araujo, J. de Goyeneche, E. Romero, J. Blesa, D. Villanueva, and O. Nieto-Taladriz, "Improving security in WMNs with reputation systems and self-organizing maps," Journal of network and computer applications, vol. 34, 2011. doi:10.1016/j.jnca.2010.03.023
  [BibTeX] [Abstract] [Download PDF]
  

  One of the most important problems of {WMNs}, that is even preventing them from being used in many sensitive applications, is the lack of security. To ensure security of {WMNs}, two strategies need to be adopted: embedding security mechanisms into the network protocols, and developing efficient intrusion detection and reaction systems. To date, many secure protocols have been proposed, but their role of defending attacks is very limited. We present a framework for intrusion detection in {WMNs} that is orthogonal to the network protocols. It is based on a reputation system, that allows to isolate ill-behaved nodes by rating their reputation as low, and distributed agents based on unsupervised learning algorithms (self-organizing maps), that are able to detect deviations from the normal behavior. An additional advantage of this approach is that it is quite independent of the attacks, and therefore it can detect and confine new, previously unknown, attacks. Unlike previous approaches, and due to the inherent insecurity of {WMN} nodes, we assume that confidentiality and integrity cannot be preserved for any single node.

  @article{BFM+11,
  abstract = {One of the most important problems of {WMNs}, that is even preventing them from being used in many sensitive applications, is the lack of security. To ensure security of {WMNs}, two strategies need to be adopted: embedding security mechanisms into the network protocols, and developing efficient intrusion detection and reaction systems. To date, many secure protocols have been proposed, but their role of defending attacks is very limited.
  We present a framework for intrusion detection in {WMNs} that is orthogonal to the network protocols. It is based on a reputation system, that allows to isolate ill-behaved nodes by rating their reputation as low, and distributed agents based on unsupervised learning algorithms (self-organizing maps), that are able to detect deviations from the normal behavior. An additional advantage of this approach is that it is quite independent of the attacks, and therefore it can detect and confine new, previously unknown, attacks. Unlike previous approaches, and due to the inherent insecurity of {WMN} nodes, we assume that confidentiality and integrity cannot be preserved for any single node.},
  author = {Bankovic, Zorana and Fraga, David and Moya, Jos\'{e} M. and Vallejo, Juan C. and Malag\'{o}n, Pedro and Araujo, \'{A}lvaro and de Goyeneche, Juan-Mariano and Romero, Elena and Blesa, Javier and Villanueva, Daniel and Nieto-Taladriz, Octavio},
  citeulike-article-id = {11722637},
  citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.jnca.2010.03.023},
  doi = {10.1016/j.jnca.2010.03.023},
  journal = {Journal of Network and Computer Applications},
  keywords = {greenlsi, josem, ms},
  posted-at = {2012-11-18 22:02:50},
  priority = {2},
  title = {{Improving security in WMNs with reputation systems and self-organizing maps}},
  url = {http://dx.doi.org/10.1016/j.jnca.2010.03.023},
  volume = {34},
  year = {2011}
  }

2010

• Z. Bankovic, J. C. Vallejo, P. Malagón, Á. Araujo, and J. M. Moya, "Eliminating routing protocol anomalies in wireless sensor networks using AI techniques," in Aisec, 2010, p. 8–13. doi:10.1145/1866423.1866426
  [BibTeX] [Abstract] [Download PDF]
  

  The specific nature of routing in sensor networks has made possible new sorts of attacks that can have closer insight and effect on the networks packets, the most important being the packet tampering. Routing attacks on the network level are the first step in tampering with the packets. In this work we propose a solution for detecting and eliminating these attacks that couples reputation systems with clustering techniques, namely unsupervised genetic algorithm and self-organizing maps, trained for detecting outliers in data. The algorithms use the feature space based on sequences of routing hops that provides ability of detecting wide range of attacks. We further present a flexible way of integrating the solution into targeted sensor network that can easily adapt its computational requirements to the existing network resources. The solution offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability, flexible integration, and high ability in detecting and confining attacks.

  @inproceedings{BVM+10,
  abstract = {The specific nature of routing in sensor networks has made possible new sorts of attacks that can have closer insight and effect on the networks packets, the most important being the packet tampering. Routing attacks on the network level are the first step in tampering with the packets. In this work we propose a solution for detecting and eliminating these attacks that couples reputation systems with clustering techniques, namely unsupervised genetic algorithm and self-organizing maps, trained for detecting outliers in data. The algorithms use the feature space based on sequences of routing hops that provides ability of detecting wide range of attacks. We further present a flexible way of integrating the solution into targeted sensor network that can easily adapt its computational requirements to the existing network resources. The solution offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability, flexible integration, and high ability in detecting and confining attacks.},
  author = {Bankovic, Zorana and Vallejo, Juan C. and Malag\'{o}n, Pedro and Araujo, \'{A}lvaro and Moya, Jos\'{e} M.},
  booktitle = {AISec},
  citeulike-article-id = {11733818},
  citeulike-linkout-0 = {http://dx.doi.org/10.1145/1866423.1866426},
  citeulike-linkout-1 = {http://dl.acm.org/citation.cfm?doid=1866423.1866426},
  doi = {10.1145/1866423.1866426},
  editor = {Greenstadt, Rachel},
  isbn = {978-1-4503-0088-9},
  keywords = {greenlsi, josem},
  pages = {8--13},
  posted-at = {2015-11-13 23:48:18},
  priority = {2},
  publisher = {ACM},
  title = {Eliminating routing protocol anomalies in wireless sensor networks using {AI} techniques},
  url = {http://dl.acm.org/citation.cfm?doid=1866423.1866426},
  year = {2010}
  }

• Z. Banković, J. M. Moya, Á. Araujo, D. Fraga, J. C. Vallejo, and J. de Goyeneche, "Distributed intrusion detection system for wireless sensor networks based on a reputation system coupled with kernel self-organizing maps," Integrated computer-aided engineering, vol. 17, iss. 2, p. 87–102, 2010. doi:10.3233/ICA-2010-0334
  [BibTeX] [Abstract] [Download PDF]
  

  Security of sensor networks is a complicated task, mostly due to the limited resources of sensor units. The first line of defense, i.e. encryption and authentication, is useless if an attacker has entered the system, and it is also vulnerable to side-channel attacks. Thus, a second line of defense, known as Intrusion Detection, must be added in order to detect and eliminate attacks. In the recent past, various solutions for detecting intrusions have been proposed. Most of them are able to detect only a limited number of attacks. Further, the solutions that deploy machine learning techniques exhibit higher level of flexibility and adaptability. Yet, these techniques consume significant power and computational resources. In this work we propose a distributed intrusion detection system organized as a reputation system where the reputation of each node is assigned by self-organizing maps ({SOM}) trained for detecting intrusions. The response of the system consists in assigning low reputation values to the compromised nodes rendering them isolated from the rest of the network. Further, we propose the implementation of {SOM} algorithm using the energy-efficient {SORU} (Stream Oriented Reconfigurable Unit) co-processor developed by our research group. Our solution offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability and energy efficiency. The testing results demonstrate its high potential.

  @article{BMA+13,
  abstract = {Security of sensor networks is a complicated task, mostly due to the limited resources of sensor units. The first line of defense, i.e. encryption and authentication, is useless if an attacker has entered the system, and it is also vulnerable to side-channel attacks. Thus, a second line of defense, known as Intrusion Detection, must be added in order to detect and eliminate attacks. In the recent past, various solutions for detecting intrusions have been proposed. Most of them are able to detect only a limited number of attacks. Further, the solutions that deploy machine learning techniques exhibit higher level of flexibility and adaptability. Yet, these techniques consume significant power and computational resources. In this work we propose a distributed intrusion detection system organized as a reputation system where the reputation of each node is assigned by self-organizing maps ({SOM}) trained for detecting intrusions. The response of the system consists in assigning low reputation values to the compromised nodes rendering them isolated from the rest of the network. Further, we propose the implementation of {SOM} algorithm using the energy-efficient {SORU} (Stream Oriented Reconfigurable Unit) co-processor developed by our research group. Our solution offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability and energy efficiency. The testing results demonstrate its high potential.},
  author = {Bankovi\'{c}, Zorana and Moya, Jos\'{e} M. and Araujo, \'{A}lvaro and Fraga, David and Vallejo, Juan C. and de Goyeneche, Juan-Mariano},
  citeulike-article-id = {12289896},
  citeulike-linkout-0 = {http://dx.doi.org/10.3233/ICA-2010-0334},
  day = {1},
  doi = {10.3233/ICA-2010-0334},
  journal = {Integrated Computer-Aided Engineering},
  keywords = {ami, greenlsi, josem, security},
  month = jan,
  number = {2},
  pages = {87--102},
  posted-at = {2013-04-22 08:40:29},
  priority = {2},
  title = {Distributed intrusion detection system for wireless sensor networks based on a reputation system coupled with kernel self-organizing maps},
  url = {http://dx.doi.org/10.3233/ICA-2010-0334},
  volume = {17},
  year = {2010}
  }

• M. Zapater, J. L. Risco, J. L. Ayala, and J. M. Moya, "Combined Dynamic-Static approach for Thermal-Awareness in heterogeneous data centers," in Iwia, , 2010. doi:10.1109/IWIA.2010.7
  [BibTeX] [Abstract] [Download PDF]
  

  The thermal profile of data centers plays a significant role in affecting the cooling cost and power budget of the system. While several dynamic and static approaches have been proposed so far, these have failed on considering the whole picture. This paper proposes a combined static and dynamic approach that shows the benefits of the efficient scheduling strategies on leading to thermal-efficient floorplans. The devised methodology comes out with a placement of processors and task scheduling for a heterogeneous system, where the main thermal metrics (maximum temperature and thermal gradient) have been optimized.

  @inbook{ZRAM12,
  abstract = {The thermal profile of data centers plays a significant role in affecting the cooling cost and power budget of the system. While several dynamic and static approaches have been proposed so far, these have failed on considering the whole picture. This paper proposes a combined static and dynamic approach that shows the benefits of the efficient scheduling strategies on leading to thermal-efficient floorplans. The devised methodology comes out with a placement of processors and task scheduling for a heterogeneous system, where the main thermal metrics (maximum temperature and thermal gradient) have been optimized.},
  author = {Zapater, Marina and Risco, Jose L. and Ayala, Jose L. and Moya, Jose M.},
  booktitle = {IWIA},
  citeulike-article-id = {11737377},
  citeulike-linkout-0 = {http://dx.doi.org/10.1109/IWIA.2010.7},
  doi = {10.1109/IWIA.2010.7},
  keywords = {datacenters, greenlsi, josem},
  posted-at = {2012-11-22 15:27:59},
  priority = {2},
  title = {Combined {Dynamic-Static} Approach for {Thermal-Awareness} in Heterogeneous Data Centers},
  url = {http://dx.doi.org/10.1109/IWIA.2010.7},
  year = {2010}
  }

• Z. Banković, D. Fraga, J. M. Moya, J. C. Vallejo, Á. Araujo, P. Malagón, J. Goyeneche, D. Villanueva, E. Romero, and J. Blesa, "Detecting and confining sybil attack in wireless sensor networks based on reputation systems coupled with self-organizing maps," in Artificial intelligence applications and innovations, H. Papadopoulos, A. Andreou, and M. Bramer, Eds., Springer Berlin Heidelberg, 2010, vol. 339, p. 311–318. doi:10.1007/978-3-642-16239-8_41
  [BibTeX] [Abstract] [Download PDF]
  

  The Sybil attack is one of the most aggressive and evasive attacks in sensor networks that can affect on many aspects of network functioning. Thus, its efficient detection is of highest importance. In order to resolve this issue, in this work we propose to couple reputation systems with agents based on self-organizing map algorithm trained for detecting outliers in data. The response of the system consists in assigning low reputation values to the compromised node rendering them isolated from the rest of the network. The main improvement of this work consists in the way of calculating reputation, which is more flexible and discriminative in distinguishing attacks from normal behavior. Self-organizing map algorithm deploys feature space based on sequences of sensor outputs. Our solution offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability and low consumption. The testing results demonstrate its high ability in detecting and confining Sybil attack.

  @incollection{BFM+10,
  abstract = {The Sybil attack is one of the most aggressive and evasive attacks in sensor networks that can affect on many aspects of network functioning. Thus, its efficient detection is of highest importance. In order to resolve this issue, in this work we propose to couple reputation systems with agents based on self-organizing map algorithm trained for detecting outliers in data. The response of the system consists in assigning low reputation values to the compromised node rendering them isolated from the rest of the network. The main improvement of this work consists in the way of calculating reputation, which is more flexible and discriminative in distinguishing attacks from normal behavior. Self-organizing map algorithm deploys feature space based on sequences of sensor outputs. Our solution offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability and low consumption. The testing results demonstrate its high ability in detecting and confining Sybil attack.},
  author = {Bankovi\'{c}, Zorana and Fraga, David and Moya, Jos\'{e} M. and Vallejo, Juan C. and Araujo, \'{A}lvaro and Malag\'{o}n, Pedro and Goyeneche, Juan-Mariano and Villanueva, Daniel and Romero, Elena and Blesa, Javier},
  booktitle = {Artificial Intelligence Applications and Innovations},
  citeulike-article-id = {11723369},
  citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-642-16239-8\_41},
  doi = {10.1007/978-3-642-16239-8\_41},
  editor = {Papadopoulos, Harris and Andreou, AndreasS and Bramer, Max},
  keywords = {detection, greenlsi, josem, maps, networks, outlier, reputation, self-organizing, sensor, system, wireless},
  pages = {311--318},
  posted-at = {2012-11-18 23:56:53},
  priority = {0},
  publisher = {Springer Berlin Heidelberg},
  series = {IFIP Advances in Information and Communication Technology},
  title = {Detecting and Confining Sybil Attack in Wireless Sensor Networks Based on Reputation Systems Coupled with Self-organizing Maps},
  url = {http://dx.doi.org/10.1007/978-3-642-16239-8\_41},
  volume = {339},
  year = {2010}
  }

• Z. Banković, J. C. Vallejo, P. Malagón, Á. Araujo, and J. M. Moya, "Eliminating routing protocol anomalies in wireless sensor networks using AI techniques," in ACM Conference on Computer and Communications Security, 2010. doi:10.1145/1866423.1866426
  [BibTeX] [Abstract] [Download PDF]
  

  The specific nature of routing in sensor networks has made possible new sorts of attacks that can have closer insight and effect on the networks packets, the most important being the packet tampering. Routing attacks on the network level are the first step in tampering with the packets. In this work we propose a solution for detecting and eliminating these attacks that couples reputation systems with clustering techniques, namely unsupervised genetic algorithm and self-organizing maps, trained for detecting outliers in data. The algorithms use the feature space based on sequences of routing hops that provides ability of detecting wide range of attacks. We further present a flexible way of integrating the solution into targeted sensor network that can easily adapt its computational requirements to the existing network resources. The solution offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability, flexible integration, and high ability in detecting and confining attacks.

  @inproceedings{BVM+10,
  abstract = {The specific nature of routing in sensor networks has made possible new sorts of attacks that can have closer insight and effect on the networks packets, the most important being the packet tampering. Routing attacks on the network level are the first step in tampering with the packets. In this work we propose a solution for detecting and eliminating these attacks that couples reputation systems with clustering techniques, namely unsupervised genetic algorithm and self-organizing maps, trained for detecting outliers in data. The algorithms use the feature space based on sequences of routing hops that provides ability of detecting wide range of attacks. We further present a flexible way of integrating the solution into targeted sensor network that can easily adapt its computational requirements to the existing network resources. The solution offers many benefits: scalable solution, fast response to adversarial activities, ability to detect unknown attacks, high adaptability, flexible integration, and high ability in detecting and confining attacks.},
  author = {Bankovi\'{c}, Zorana and Vallejo, Juan C. and Malag\'{o}n, Pedro and Araujo, \'{A}lvaro and Moya, Jos\'{e} M.},
  booktitle = {{ACM Conference on Computer and Communications Security}},
  citeulike-article-id = {11722639},
  citeulike-linkout-0 = {http://dx.doi.org/10.1145/1866423.1866426},
  doi = {10.1145/1866423.1866426},
  keywords = {greenlsi, josem, ms},
  posted-at = {2012-11-18 22:02:52},
  priority = {2},
  title = {{Eliminating routing protocol anomalies in wireless sensor networks using AI techniques}},
  url = {http://dx.doi.org/10.1145/1866423.1866426},
  year = {2010}
  }

2009

• I. Recio, J. M. Moya, Á. Araujo, J. C. Vallejo, and P. Malagón, "Analysis and design of an object tracking service for intelligent environments," in Iwann (2), 2009, p. 914–921. doi:10.1007/978-3-642-02481-8_139
  [BibTeX] [Abstract] [Download PDF]
  

  This paper describes the design and implementation of an object tracking service for indoor environments. First, the wireless indoor location estimation technology is overviewed presenting advantages and disadvantages. Second, the methodology of the study is presented. To estimate the position we use clues inserted by location clue injectors of the system. In our architecture one of these injectors is a {ZigBee} sensor network. As location algorithm we have developed a method combining statistical techniques (particle filter) and proximity sensing (nearest neighbour) to get better efficiency. The results obtained show that a good precision and reliability can be achieved with a low-cost solution.

  @inproceedings{RMA+09,
  abstract = {This paper describes the design and implementation of an object tracking service for indoor environments. First, the wireless indoor location estimation technology is overviewed presenting advantages and disadvantages. Second, the methodology of the study is presented. To estimate the position we use clues inserted by location clue injectors of the system. In our architecture one of these injectors is a {ZigBee} sensor network. As location algorithm we have developed a method combining statistical techniques (particle filter) and proximity sensing (nearest neighbour) to get better efficiency. The results obtained show that a good precision and reliability can be achieved with a low-cost solution.},
  author = {Recio, Ignacio and Moya, Jos\'{e} M. and Araujo, \'{A}lvaro and Vallejo, Juan C. and Malag\'{o}n, Pedro},
  booktitle = {IWANN (2)},
  citeulike-article-id = {11733951},
  citeulike-linkout-0 = {http://link.springer.com/chapter/10.1007\%2F978-3-642-02481-8\_139},
  citeulike-linkout-1 = {http://dx.doi.org/10.1007/978-3-642-02481-8\_139},
  doi = {10.1007/978-3-642-02481-8\_139},
  editor = {Omatu, Sigeru and Rocha, Miguel and Bravo, Jos\'{e} and Riverola, Florentino F. and Corchado, Emilio and Bustillo, Andr\'{e}s and Corchado, Juan M.},
  keywords = {greenlsi, josem},
  pages = {914--921},
  posted-at = {2015-11-13 23:47:01},
  priority = {2},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {Analysis and Design of an Object Tracking Service for Intelligent Environments},
  url = {http://link.springer.com/chapter/10.1007\%2F978-3-642-02481-8\_139},
  volume = {5518},
  year = {2009}
  }

• J. M. Moya, J. C. Vallejo, P. Malagón, Á. Araujo, J. de Goyeneche, and O. Nieto-Taladriz, "A scalable security framework for reliable AmI applications based on untrusted sensors," in Wwic, 2009, p. 73–84. doi:10.1007/978-3-642-02118-3_7
  [BibTeX] [Abstract] [Download PDF]
  

  Security in Ambient Intelligence ({AmI}) poses too many challenges due to the inherently insecure nature of wireless sensor nodes. However, there are two characteristics of these environments that can be used effectively to prevent, detect, and confine attacks: redundancy and continuous adaptation. In this article we propose a global strategy and a system architecture to cope with security issues in {AmI} applications at different levels. Unlike in previous approaches, we assume an individual wireless node is vulnerable. We present an agent-based architecture with supporting services that is proven to be adequate to detect and confine common attacks. Decisions at different levels are supported by a trust-based framework with good and bad reputation feedback while maintaining resistance to bad-mouthing attacks. We also propose a set of services that can be used to handle identification, authentication, and authorization in intelligent ambients. The resulting approach takes into account practical issues, such as resource limitation, bandwidth optimization, and scalability.

  @inproceedings{MVM+09,
  abstract = {Security in Ambient Intelligence ({AmI}) poses too many challenges due to the inherently insecure nature of wireless sensor nodes. However, there are two characteristics of these environments that can be used effectively to prevent, detect, and confine attacks: redundancy and continuous adaptation. In this article we propose a global strategy and a system architecture to cope with security issues in {AmI} applications at different levels. Unlike in previous approaches, we assume an individual wireless node is vulnerable.
  We present an agent-based architecture with supporting services that is proven to be adequate to detect and confine common attacks. Decisions at different levels are supported by a trust-based framework with good and bad reputation feedback while maintaining resistance to bad-mouthing attacks. We also propose a set of services that can be used to handle identification, authentication, and authorization in intelligent ambients.
  The resulting approach takes into account practical issues, such as resource limitation, bandwidth optimization, and scalability.},
  author = {Moya, Jos\'{e} M. and Vallejo, Juan C. and Malag\'{o}n, Pedro and Araujo, \'{A}lvaro and de Goyeneche, Juan-Mariano and Nieto-Taladriz, Octavio},
  booktitle = {WWIC},
  citeulike-article-id = {11733964},
  citeulike-linkout-0 = {http://dx.doi.org/10.1007/978-3-642-02118-3\_7},
  citeulike-linkout-1 = {http://link.springer.com/chapter/10.1007\%2F978-3-642-02118-3\_7},
  doi = {10.1007/978-3-642-02118-3\_7},
  editor = {van den Berg, Hans and Heijenk, Geert J. and Osipov, Evgeny and Staehle, Dirk},
  keywords = {greenlsi, josem, security},
  pages = {73--84},
  posted-at = {2012-11-22 15:35:11},
  priority = {2},
  publisher = {Springer},
  series = {Lecture Notes in Computer Science},
  title = {A Scalable Security Framework for Reliable {AmI} Applications Based on Untrusted Sensors},
  url = {http://link.springer.com/chapter/10.1007\%2F978-3-642-02118-3\_7},
  volume = {5546},
  year = {2009}
  }

• J. M. Moya, J. C. Vallejo, D. Fraga, Á. Araujo, D. Villanueva, and J. de Goyeneche, "Using Reputation Systems and Non-Deterministic Routing to Secure Wireless Sensor Networks," Sensors, vol. 9, 2009. doi:10.3390/s90503958
  [BibTeX] [Abstract] [Download PDF]
  

  Security in wireless sensor networks is difficult to achieve because of the resource limitations of the sensor nodes. We propose a trust-based decision framework for wireless sensor networks coupled with a non-deterministic routing protocol. Both provide a mechanism to effectively detect and confine common attacks, and, unlike previous approaches, allow bad reputation feedback to the network. This approach has been extensively simulated, obtaining good results, even for unrealistically complex attack scenarios.

  @article{MVF+09,
  abstract = {Security in wireless sensor networks is difficult to achieve because of the resource limitations of the sensor nodes. We propose a trust-based decision framework for wireless sensor networks coupled with a non-deterministic routing protocol. Both provide a mechanism to effectively detect and confine common attacks, and, unlike previous approaches, allow bad reputation feedback to the network. This approach has been extensively simulated, obtaining good results, even for unrealistically complex attack scenarios.},
  author = {Moya, Jos\'{e} M. and Vallejo, Juan C. and Fraga, David and Araujo, \'{A}lvaro and Villanueva, Daniel and de Goyeneche, Juan-Mariano},
  citeulike-article-id = {11722641},
  citeulike-linkout-0 = {http://dx.doi.org/10.3390/s90503958},
  doi = {10.3390/s90503958},
  journal = {Sensors},
  keywords = {greenlsi, josem, ms},
  posted-at = {2012-11-18 22:02:53},
  priority = {2},
  title = {{Using Reputation Systems and Non-Deterministic Routing to Secure Wireless Sensor Networks}},
  url = {http://dx.doi.org/10.3390/s90503958},
  volume = {9},
  year = {2009}
  }

• J. M. Moya, Á. Araujo, Z. Banković, J. de Goyeneche, J. C. Vallejo, P. Malagón, D. Villanueva, D. Fraga, E. Romero, and J. Blesa, "Improving Security for SCADA Sensor Networks with Reputation Systems and Self-Organizing Maps," Sensors, vol. 9, 2009. doi:10.3390/s91109380
  [BibTeX] [Abstract] [Download PDF]
  

  The reliable operation of modern infrastructures depends on computerized systems and Supervisory Control and Data Acquisition ({SCADA}) systems, which are also based on the data obtained from sensor networks. The inherent limitations of the sensor devices make them extremely vulnerable to cyberwarfare/cyberterrorism attacks. In this paper, we propose a reputation system enhanced with distributed agents, based on unsupervised learning algorithms (self-organizing maps), in order to achieve fault tolerance and enhanced resistance to previously unknown attacks. This approach has been extensively simulated and compared with previous proposals.

  @article{MAB+09,
  abstract = {The reliable operation of modern infrastructures depends on computerized systems and Supervisory Control and Data Acquisition ({SCADA}) systems, which are also based on the data obtained from sensor networks. The inherent limitations of the sensor devices make them extremely vulnerable to cyberwarfare/cyberterrorism attacks. In this paper, we propose a reputation system enhanced with distributed agents, based on unsupervised learning algorithms (self-organizing maps), in order to achieve fault tolerance and enhanced resistance to previously unknown attacks. This approach has been extensively simulated and compared with previous proposals.},
  author = {Moya, Jos\'{e} M. and Araujo, \'{A}lvaro and Bankovi\'{c}, Zorana and de Goyeneche, Juan-Mariano and Vallejo, Juan C. and Malag\'{o}n, Pedro and Villanueva, Daniel and Fraga, David and Romero, Elena and Blesa, Javier},
  citeulike-article-id = {11722640},
  citeulike-linkout-0 = {http://dx.doi.org/10.3390/s91109380},
  doi = {10.3390/s91109380},
  journal = {Sensors},
  keywords = {greenlsi, josem, ms},
  posted-at = {2012-11-18 22:02:53},
  priority = {2},
  title = {{Improving Security for SCADA Sensor Networks with Reputation Systems and Self-Organizing Maps}},
  url = {http://dx.doi.org/10.3390/s91109380},
  volume = {9},
  year = {2009}
  }