Multi-Objective Optimization of Intrusion Detection Systems for Wireless Sensor Networks

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Publikace nespadá pod Filozofickou fakultu, ale pod Fakultu informatiky. Oficiální stránka publikace je na webu muni.cz.
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STEHLÍK Martin SALEH Adam STETSKO Andriy MATYÁŠ Václav

Rok publikování 2013
Druh Článek ve sborníku
Konference Advances in Artificial Life, ECAL 2013, Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living Systems
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
www http://mitpress.mit.edu/sites/default/files/titles/content/ecal13/ch082.html
Doi http://dx.doi.org/10.7551/978-0-262-31709-2-ch082
Obor Informatika
Klíčová slova Evolutionary algorithm; Multi-objective evolutionary algorithm; Optimization; Wireless sensor network; Intrusion detection system
Popis Intrusion detection is an essential mechanism to protect wireless sensor networks against internal attacks that are relatively easy and not expensive to mount in these networks. Recently, we proposed, implemented and tested a framework that helps a network operator to find a trade-off between detection accuracy and usage of resources that are usually highly constrained in wireless sensor networks. We used a single-objective optimization evolutionary algorithm for this purpose. This approach, however, has its limitations. In order to eliminate them, we show benefits of multi-objective evolutionary algorithms for intrusion detection parametrization and examine two multi-objective evolutionary algorithms (NSGA-II and SPEA2). Our examination focuses on the impact of an evolutionary algorithm (and its parameters) on the optimality of found solutions, the speed of convergence and the number of evaluations.
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