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Thesis ( M.Sc. (Computer Science)) -- University of Limpopo, 2019 / Cognitive radio network, which enables dynamic spectrum access, addresses the shortage of radio spectrum caused by ever-increasing wireless technology. This allows efficient utilisation of underutilised licenced spectrum by allowing cognitive radios to opportunistically make use of available licenced spectrum. Cognitive radios (CR), also known as secondary users, must constantly sense the spectrum band to avoid interfering with the transmission of the licenced users, known as primary users. Cognitive radios must cooperate in sensing the spectrum environment to avoid environmental issues that can affect the spectrum sensing. However, cooperative spectrum sensing is vulnerable to Byzantine attacks where selfish CR falsify the spectrum reports. Hence, there is a need to design and implement a defence mechanism that will thwart the Byzantine attacks and guarantee correct available spectrum access decisions. The use of extreme studentized deviate (ESD) test together with consensus algorithms are proposed in this study to combat the results of the availability of Byzantine attack in a cognitive radio network. The ESD test was used to detect and isolate falsified reports from selfish cognitive radios during the information sharing phase. The consensus algorithm was used to combine sensing reports at each time k to arrive at a consensus value which will be used to decide the spectrum availability. The proposed scheme, known extreme studentized cooperative consensus spectrum sensing (ESCCSS), was implemented in an ad hoc cognitive radio networks environment where the use of a data fusion centre (DFC) is not required. Cognitive radios make their own data fusion and make the final decision about the availability of the spectrum on their sensed reports and reports from their neighbouring nodes without any assistance from the fusion centre. MATLAB was used to implement and simulate the proposed scheme. We compared our scheme with Attack-Proof Cooperative Spectrum Sensing to check its effectiveness in combating the effect of byzantine attack.

In this dissertation, we consider scheduling distributed soft real-time tasks in unreliable (e.g., those with arbitrary node and network failures) and untrustworthy systems (e.g., those with Byzantine node behaviors). We present a distributed real-time scheduling algorithm called Gamma. Gamma considers a distributed (i.e., multi-node) task model where tasks are subject to Time/Utility Function (or TUF) end-to-end time constraints, and the scheduling optimality criterion of maximizing the total accrued utility. The algorithm makes three novel contributions. First, Gamma uses gossip for reliably propagating task scheduling parameters and for discovering task execution nodes. Second, Gamma achieves distributed real-time mutual exclusion in unreliable environments. Third, the algorithm guards against potential disruption of message propagation due to Byzantine attacks using a mechanism called Launcher-Attacker-Infective-Susceptible-Immunized-Removed-Consumer (or LAISIRC). By doing so, the algorithm schedules tasks with probabilistic termination-time satisfactions, despite system unreliability and untrustworthiness. We analytically establish several timeliness and non-timeliness properties of the algorithm including probabilistic end-to-end task termination time satisfactions, optimality of message overheads, mutual exclusion guarantees, and the mathematical model of the LAISIRC mechanism. We conducted simulation-based experimental studies and compared Gamma with its competitors. Our experimental studies reveal that Gamma's scheduling algorithm accrues greater utility and satisfies a greater number of deadlines than do competitor algorithms (e.g., HVDF) by as much as 47% and 45%, respectively. LAISIRC is more tolerant to Byzantine attacks than competitor protocols (e.g., Path Verification) by obtaining as much as 28% higher correctness ratio. Gamma's mutual exclusion algorithm accrues greater utility than do competitor algorithms (e.g., EDF-Sigma) by as much as 25%. Further, we implemented the basic Gamma algorithm in the Emulab/ChronOS 250-node testbed, and measured the algorithm's performance. Our implementation measurements validate our theoretical analysis and the algorithm's effectiveness and robustness. / Ph. D.