FUZZY VOTING FOR ANOMALY DETECTION IN CLUSTER-BASED MOBILE AD HOC NETWORKS

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RAHMANIMANESH M.; JALILI S.

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Paper Information

Journal: NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR Year:2013 | Volume:10 | Issue:2 Page(s): 86-100

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Information Journal Paper

Title

FUZZY VOTING FOR ANOMALY DETECTION IN CLUSTER-BASED MOBILE AD HOC NETWORKS

Author(s)

RAHMANIMANESH M. | JALILI S. | Issue Writer Certificate

Keywords

MOBILE AD HOC NETWORKQ2

ANOMALY DETECTIONQ2

AODV ANALYSISQ3

ATTACK ANALYSISQ3

FUSION OF ONE-CLASS CLASSIFIERSQ3

FUZZY VOTINGQ3

Abstract

Abstract: In this paper, an ATTACK ANALYSIS and detection method in cluster-based MOBILE AD HOC NETWORKs with AODV routing protocol is proposed. The proposed method uses the ANOMALY DETECTION approach for detecting attacks in which the required features for describing the normal behavior of AODV protocol are defined via step by step analysis of AODV protocol and independent of any attack. In order to learn the normal behavior of AODV, a FUZZY VOTING method is used for combining support vector data description (SVDD), mixture of Gaussians (MoG), and self-organizing maps (SOM) one-class classifiers and the combined model is utilized to partially detect the attacks in cluster members. The votes of cluster members are periodically transmitted to the cluster head and final decision on attack detection is carried out in the cluster head. In the proposed method, a FUZZY VOTING method is used for aggregating the votes of cluster members in the cluster head by which the performance of the method improves significantly in detecting blackhole, rushing, route error fabrication, packet replication, and wormhole attacks. In this paper, an ATTACK ANALYSIS method based on feature sensitivity ranking is also proposed that determines which features are influenced more by the mentioned attacks. This sensitivity ranking leads to the detection of the types of attacks launched on the network.

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APA: Copy

RAHMANIMANESH, M., & JALILI, S.. (2013). FUZZY VOTING FOR ANOMALY DETECTION IN CLUSTER-BASED MOBILE AD HOC NETWORKS. NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR, 10(2), 86-100. SID. https://sid.ir/paper/228435/en

Vancouver: Copy

RAHMANIMANESH M., JALILI S.. FUZZY VOTING FOR ANOMALY DETECTION IN CLUSTER-BASED MOBILE AD HOC NETWORKS. NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR[Internet]. 2013;10(2):86-100. Available from: https://sid.ir/paper/228435/en

IEEE: Copy

M. RAHMANIMANESH, and S. JALILI, “FUZZY VOTING FOR ANOMALY DETECTION IN CLUSTER-BASED MOBILE AD HOC NETWORKS,” NASHRIYYAH -I MUHANDISI -I BARQ VA MUHANDISI -I KAMPYUTAR -I IRAN, B- MUHANDISI -I KAMPYUTAR, vol. 10, no. 2, pp. 86–100, 2013, [Online]. Available: https://sid.ir/paper/228435/en

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