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

Shahaboddin Shamshirband, Ahmed Patel, Nor Badrul Anuar, Miss Laiha Mat Kiah, Ajith Abraham

    Research output: Contribution to journalArticle

    90 Citations (Scopus)

    Abstract

    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 method is 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 using NS-2 simulator. The model is subsequently compared against other existing soft computing methods, such as fuzzy logic controller, Q-learning, and fuzzy Q-learning, in terms of detection accuracy, counter-defense, network lifetime and energy consumption, to demonstrate its efficiency and viability. The proposed models attack detection and defense accuracy yield a greater improvement than existing above-mentioned machine learning methods. In contrast to the Markovian game theoretic, the proposed model operates better in terms of successful defense rate.

    Original languageEnglish
    Pages (from-to)228-241
    Number of pages14
    JournalEngineering Applications of Artificial Intelligence
    Volume32
    DOIs
    Publication statusPublished - 2014

    Fingerprint

    Wireless sensor networks
    Base stations
    Soft computing
    Game theory
    Intrusion detection
    Learning algorithms
    Fuzzy logic
    Learning systems
    Energy utilization
    Simulators
    Controllers

    Keywords

    • Cooperative game IDPS
    • Fuzzy Q-learning
    • Game theory
    • Intrusion detection and prevention systems
    • Security
    • WSN

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Control and Systems Engineering
    • Electrical and Electronic Engineering

    Cite this

    Cooperative game theoretic approach using fuzzy Q-learning for detecting and preventing intrusions in wireless sensor networks. / Shamshirband, Shahaboddin; Patel, Ahmed; Anuar, Nor Badrul; Kiah, Miss Laiha Mat; Abraham, Ajith.

    In: Engineering Applications of Artificial Intelligence, Vol. 32, 2014, p. 228-241.

    Research output: Contribution to journalArticle

    Shamshirband, Shahaboddin ; Patel, Ahmed ; Anuar, Nor Badrul ; Kiah, Miss Laiha Mat ; Abraham, Ajith. / Cooperative game theoretic approach using fuzzy Q-learning for detecting and preventing intrusions in wireless sensor networks. In: Engineering Applications of Artificial Intelligence. 2014 ; Vol. 32. pp. 228-241.
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