Becas cátedra bq Febrero 2014

Dentro de las actividades de la cátedra bq se contempla el establecimiento de un programa de becas en áreas de interés para la empresa y que complementen el proceso formativo de los estudiantes.

Por lo tanto, se lanza esta convocatoria de becas para el presente curso académico.

Fecha de inicio de las becas: preferiblemente el 7 de Marzo de 2014

Fecha límite de recepción de CV: 28 de Febrero de 2014

 

Posibilidad de realizar el Proyecto Fin de Carrera, Trabajo Fin de Máster, Proyecto Fin de Grado y prácticas en empresas.

 Interesados enviar un correo electrónico con el Curriculum Vitae indicando en el asunto [Becas cátedra bq] a las siguientes personas:

Silvia Rodríguez Jiménez:  silvia.jimenez@bqreaders.com

Alvaro Araujo: araujo@die.upm.es

bq-catedra-logo

Oferta de Becas Febrero 2014

Becas cátedra bq

Dentro de las actividades de la cátedra bq se contempla el establecimiento de un programa de becas en áreas de interés para la empresa y que complementen el proceso formativo de los estudiantes.

Por lo tanto, se lanza esta convocatoria de becas para el presente curso académico.

Fecha de inicio de las becas: preferiblemente el 1 de Noviembre de 2013

Duración: 6 meses

Dedicación: 4 horas/día

Remuneración: 500 € / mes

Posibilidad de realizar el Proyecto Fin de Carrera, Trabajo Fin de Máster, Proyecto Fin de Grado y prácticas en empresas.

 

Interesados enviar un correo electrónico con el Curriculum Vitae indicando en el asunto [Becas cátedra bq] a las siguientes personas:

 

Silvia Rodríguez Jiménez:  silvia.jimenez@bqreaders.com

Alvaro Araujo: araujo@die.upm.es

Convocatoria de Becas

Improving Security in WMNs with Reputation Systems and Self-Organizing Maps

Title: Improving Security in WMNs with Reputation Systems and Self-Organizing Maps
Authors: Z. Bankovic, D. Fraga, José M. Moya, J.C. Vallejo, P. Malagón, A. Araujo, J.M. de Goyeneche, E. Romero, J. Blesa, D. Villanueva, O. Nieto-Taladriz
Published in: Journal of Network and Computer Applications, Special Issue “Wireless Mesh Networks”ISSN : 1084–8045
Date of Publication: April 2010
Digital Object Identifier : 10.1016/j.jnca.2010.03.023
Web: http://www.sciencedirect.com/science/article/pii/S1084804510000585

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. The cloud vulnerability scanning tool is what is needed to make sure one safeguards their data.

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.

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Using Reputation Systems and Non-Deterministic Routing to Secure Wireless Sensor Networks

Title: Using Reputation Systems and Non-Deterministic Routing to Secure Wireless Sensor Networks
Authors: José M. Moya, J.C. Vallejo, D. Fraga, A. Araujo, D. Villanueva,J.M. de Goyeneche
Published in: Sensors, Vol 9
ISSN : 1424–8220
Date of Publication: May 2009
Digital Object Identifier : 10.3390/s90503958
Web: http://www.mdpi.com/1424-8220/9/5/3958

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.

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Distributed Intrusion Detection System for Wireless Sensor Networks based on a Reputation System coupled with Kernel Self-Organizing Maps

Title: Distributed Intrusion Detection System for Wireless Sensor Networks based on a Reputation System coupled with Kernel Self-Organizing Maps
Authors: Z. Bankovic´, J.M. Moya, A. Araujo, D. Fraga, J.C. Vallejo, J.M. de Goyeneche
Published in: Integrated Computer-Aided Engineering, Vol 17
ISSN : 1069–2509
Date of Publication: April 2010
Digital Object Identifier : 10.3233/ICA-2010-0334
Web: http://iospress.metapress.com/content/67t2t65423226255/

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.

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