Bio-inspired enhancement of reputation systems for intelligent environments

Bankovic, Zorana; Fraga Aydillo, David; Moya Fernández, José Manuel; Vallejo López, Juan Carlos; Malagón Marzo, Pedro José; Araujo Pinto, Álvaro; Goyeneche, Juan Mariano de; Romero Perales, Elena; Blesa Martínez, Javier; Villanueva González, Daniel y Nieto-Taladriz García, Octavio (2013). Bio-inspired enhancement of reputation systems for intelligent environments. "Information Sciences", v. 222 ; pp. 99-112. ISSN 0020-0255. https://doi.org/10.1016/j.ins.2011.07.032.

Descripción

Título: Bio-inspired enhancement of reputation systems for intelligent environments
Autor/es:
  • Bankovic, Zorana
  • Fraga Aydillo, David
  • Moya Fernández, José Manuel
  • Vallejo López, Juan Carlos
  • Malagón Marzo, Pedro José
  • Araujo Pinto, Álvaro
  • Goyeneche, Juan Mariano de
  • Romero Perales, Elena
  • Blesa Martínez, Javier
  • Villanueva González, Daniel
  • Nieto-Taladriz García, Octavio
Tipo de Documento: Artículo
Título de Revista/Publicación: Information Sciences
Fecha: Febrero 2013
Volumen: 222
Materias:
Palabras Clave Informales: Ambient intelligence; Security; Reputation system; Unsupervised techniques; Self-organizing maps; Genetic algorithms
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Ingeniería Electrónica
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

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.

Más información

ID de Registro: 28976
Identificador DC: http://oa.upm.es/28976/
Identificador OAI: oai:oa.upm.es:28976
Identificador DOI: 10.1016/j.ins.2011.07.032
URL Oficial: http://www.sciencedirect.com/science/article/pii/S0020025511003641
Depositado por: Memoria Investigacion
Depositado el: 04 Jun 2014 17:01
Ultima Modificación: 01 Mar 2015 23:56
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