Browsing by Author "Escudero-Andreu, G."

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    A Data Fusion Technique to Detect Wireless Network Virtual Jamming Attacks
    (IEEE, 2015-11-12) Escudero-Andreu, G.; Kyriakopoulos, Konstantinos; Aparicio-Navarro, Francisco J.; Parish, David J.; Santoro, D.; Vadursi, M.
    Wireless communications are potentially exposed to jamming due to the openness of the medium and, in particular, to virtual jamming, which allows more energy-efficient attacks. In this paper we tackle the problem of virtual jamming attacks on IEEE 802.11 networks and present a data fusion solution for the detection of a type of virtual jamming attack (namely, NAV attacks), based on the real-time monitoring of a set of metrics. The detection performance is evaluated in a number of real scenarios.
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    A Hybrid Intrusion Detection System for Virtual Jamming Attacks on Wireless Networks
    (Elsevier, 2017-05-17) Aparicio-Navarro, Francisco J.; Kyriakopoulos, Konstantinos; Escudero-Andreu, G.; Santoro, D.; Vadursi, M.; Parish, D. J.
    Wireless communications are vulnerable to certain number of cyber-attacks and intrusion attempts due to the intrinsic openness of the communication channel. Virtual jamming attack stands out among other attacks. This type of attack is easy to implement, energy-efficient to be launched, and represents one of the most important threats to the security of wireless networks. As the complexity of the attacks keeps increasing, new and more robust detection mechanisms need to be developed. A number of Network Intrusion Detection Systems (NIDSs) have been presented in the literature to detect this type of attack. To tackle the problem of virtual jamming attacks on IEEE 802.11 networks, we present a novel Hybrid-NIDS (H-NIDS) based on Dempster-Shafer (DS) Theory of Evidence. The proposed method aims at combining the advantages of signature-based and anomaly-based NIDSs. The performance of the proposed solution has been experimentally evaluated with multiple scenarios in an IEEE 802.11 network.