Bio-inspired enhancement of reputation systems for intelligent environments

Bankovic, Zorana and Fraga Aydillo, David and Moya Fernández, José Manuel and Vallejo López, Juan Carlos and Malagón Marzo, Pedro José and Araujo Pinto, Álvaro and Goyeneche, Juan Mariano de and Romero Perales, Elena and Blesa Martínez, Javier and Villanueva González, Daniel and 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.

Description

Title: Bio-inspired enhancement of reputation systems for intelligent environments
Author/s:
  • 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
Item Type: Article
Título de Revista/Publicación: Information Sciences
Date: February 2013
Volume: 222
Subjects:
Freetext Keywords: Ambient intelligence; Security; Reputation system; Unsupervised techniques; Self-organizing maps; Genetic algorithms
Faculty: E.T.S.I. Telecomunicación (UPM)
Department: Ingeniería Electrónica
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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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.

More information

Item ID: 28976
DC Identifier: http://oa.upm.es/28976/
OAI Identifier: oai:oa.upm.es:28976
DOI: 10.1016/j.ins.2011.07.032
Official URL: http://www.sciencedirect.com/science/article/pii/S0020025511003641
Deposited by: Memoria Investigacion
Deposited on: 04 Jun 2014 17:01
Last Modified: 01 Mar 2015 23:56
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