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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F13%3A00066312" target="_blank" >RIV/00216224:14330/13:00066312 - isvavai.cz</a>

Výsledek na webu

<a href="http://mitpress.mit.edu/sites/default/files/titles/content/ecal13/ch082.html" target="_blank" >http://mitpress.mit.edu/sites/default/files/titles/content/ecal13/ch082.html</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.7551/978-0-262-31709-2-ch082" target="_blank" >10.7551/978-0-262-31709-2-ch082</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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 theimpact of an evolutionary algorithm (and its parameters) on the optimality of found solutions, the speed of convergence and the number of evaluations.

Název v anglickém jazyce

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

Popis výsledku anglicky

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 theimpact of an evolutionary algorithm (and its parameters) on the optimality of found solutions, the speed of convergence and the number of evaluations.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GAP202%2F11%2F0422" target="_blank" >GAP202/11/0422: Bezpečnostní protokoly podporující soukromí a detekce průniku v bezdrátových senzorových sítích</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Advances in Artificial Life, ECAL 2013, Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living Systems

ISBN

9780262317092

ISSN

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e-ISSN

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Počet stran výsledku

8

Strana od-do

569-576

Název nakladatele

MIT Press

Místo vydání

Cambridge, MA 02142-1493 USA

Místo konání akce

Taormina, Italy

Datum konání akce

2. 9. 2013

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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