Cooperative game theoretic approach using fuzzy Q-learning for detecting and preventing intrusions in wireless sensor networks

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F14%3A86092820" target="_blank" >RIV/61989100:27240/14:86092820 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1016/j.engappai.2014.02.001" target="_blank" >http://dx.doi.org/10.1016/j.engappai.2014.02.001</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.engappai.2014.02.001" target="_blank" >10.1016/j.engappai.2014.02.001</a>

Result language

angličtina

Original language name

Cooperative game theoretic approach using fuzzy Q-learning for detecting and preventing intrusions in wireless sensor networks

Original language description

Owing to the distributed nature of denial-of-service attacks, it is tremendously challenging to detect such malicious behavior using traditional intrusion detection systems in Wireless Sensor Networks (WSNs). In the current paper, a game theoretic methodis introduced, namely cooperative Game-based Fuzzy Q-learning (G-FQL). G-FQL adopts a combination of both the game theoretic approach and the fuzzy Q-learning algorithm in WSNs. It is a three-player strategy game consisting of sink nodes, a base station, and an attacker. The game performs at any time a victim node in the network receives a flooding packet as a DDoS attack beyond a specific alarm event threshold in WSN. The proposed model implements cooperative defense counter-attack scenarios for the sink node and the base station to operate as rational decision-maker players through a game theory strategy. In order to evaluate the performance of the proposed model, the Low Energy Adaptive Clustering Hierarchy (LEACH) was simulated usi

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

IN - Informatics

OECD FORD branch

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Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2014

Confidentiality

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

Name of the periodical

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

ISSN

0952-1976

e-ISSN

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Volume of the periodical

32

Issue of the periodical within the volume

Jun

Country of publishing house

GB - UNITED KINGDOM

Number of pages

14

Pages from-to

228-241

UT code for WoS article

000336953900020

EID of the result in the Scopus database

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