Yes / 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. / Gulf Science, Innovation and Knowledge Economy Programme of the U.K. Government under UK-Gulf Institutional Link Grant IL 279339985 and in part by the Engineering and Physical Sciences Research Council (EPSRC), U.K., under Grant EP/R006385/1.
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/17616 |
| Date | 24 January 2020 |
| Creators | Ghafir, Ibrahim, Kyriakopoulos, K.G., Aparicio-Navarro, F.J., Lambotharan, S., Assadhan, B., Binsalleeh, A.H. |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Article, Published version |
| Rights | This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/, CC-BY |
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