Visible to the public Bayesian decision model with trilateration for primary user emulation attack localization in cognitive radio networks

TitleBayesian decision model with trilateration for primary user emulation attack localization in cognitive radio networks
Publication TypeConference Paper
Year of Publication2017
AuthorsFihri, W. F., Ghazi, H. E., Kaabouch, N., Majd, B. A. E.
Conference Name2017 International Symposium on Networks, Computers and Communications (ISNCC)
Date Publishedmay
ISBN Number978-1-5090-4260-9
KeywordsBayes methods, Bayesian decision model, Bayesian decision theory, Channel estimation, Cognitive radio, cognitive radio networks, Cognitive Radio Security, conditional probability, decision theory, deny-of-service attack, DoS attack, licensed channel, lost function, network coding, physical network layer coding, Primary user Emulation, primary user emulation attack localization, probability, PU, PU-PUE, pubcrawl, PUE attacker, PUE position, received signal strength indication, Received signal strength indicator, Resiliency, risk management, RSSI, telecommunication security, Trilateration, trilateration technique, Uncertainty, Wireless sensor networks

Primary user emulation (PUE) attack is one of the main threats affecting cognitive radio (CR) networks. The PUE can forge the same signal as the real primary user (PU) in order to use the licensed channel and cause deny of service (DoS). Therefore, it is important to locate the position of the PUE in order to stop and avoid any further attack. Several techniques have been proposed for localization, including the received signal strength indication RSSI, Triangulation, and Physical Network Layer Coding. However, the area surrounding the real PU is always affected by uncertainty. This uncertainty can be described as a lost (cost) function and conditional probability to be taken into consideration while proclaiming if a PU/PUE is the real PU or not. In this paper, we proposed a combination of a Bayesian model and trilateration technique. In the first part a trilateration technique is used to have a good approximation of the PUE position making use of the RSSI between the anchor nodes and the PU/PUE. In the second part, a Bayesian decision theory is used to claim the legitimacy of the PU based on the lost function and the conditional probability to help to determine the existence of the PUE attacker in the uncertainty area.

Citation Keyfihri_bayesian_2017