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A basic probability assignment methodology for unsupervised wireless intrusion detection

Ghafir, Ibrahim
Kyriakopoulos, K.G.
Aparicio-Navarro, F.J.
Lambotharan, S.
Assadhan, B.
Binsalleeh, A.H.
Publication Date
2018-07-11
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Rights
This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/
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Open Access status
openAccess
Accepted for publication
2018-06-24
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Abstract
The broadcast nature of wireless local area networks has made them prone to several types of wireless injection attacks, such as Man-in-the-Middle (MitM) at the physical layer, deauthentication, and rogue access point attacks. The implementation of novel intrusion detection systems (IDSs) is fundamental to provide stronger protection against these wireless injection attacks. Since most attacks manifest themselves through different metrics, current IDSs should leverage a cross-layer approach to help toward improving the detection accuracy. The data fusion technique based on the Dempster–Shafer (D-S) theory has been proven to be an efficient technique to implement the cross-layer metric approach. However, the dynamic generation of the basic probability assignment (BPA) values used by D-S is still an open research problem. In this paper, we propose a novel unsupervised methodology to dynamically generate the BPA values, based on both the Gaussian and exponential probability density functions, the categorical probability mass function, and the local reachability density. Then, D-S is used to fuse the BPA values to classify whether the Wi-Fi frame is normal (i.e., non-malicious) or malicious. The proposed methodology provides 100% true positive rate (TPR) and 4.23% false positive rate (FPR) for the MitM attack and 100% TPR and 2.44% FPR for the deauthentication attack, which confirm the efficiency of the dynamic BPA generation methodology.
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Published version
Citation
Ghafir I, Kyriakopoulos KG, Aparicio-Navarro FJ et al (2018) A basic probability assignment methodology for unsupervised wireless intrusion detection. IEEE Access. 6: 40008-40023.
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