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Real-Time Misbehavior Detection in IEEE 802.11-Based Wireless Networks: An Analytical Approach
Jan. 2014 (vol. 13 no. 1)
pp. 146-158
Jin Tang, Illinois Institute of Technology, Chicago
Yu Cheng, Illinois Institute of Technology, Chicago
Weihua Zhuang, University of Waterloo, Waterloo
The distributed nature of the CSMA/CA-based wireless protocols, for example, the IEEE 802.11 distributed coordinated function (DCF), allows malicious nodes to deliberately manipulate their backoff parameters and, thus, unfairly gain a large share of the network throughput. In this paper, we first design a real-time backoff misbehavior detector, termed as the fair share detector (FS detector), which exploits the nonparametric cumulative sum (CUSUM) test to quickly find a selfish malicious node without any a priori knowledge of the statistics of the selfish misbehavior. While most of the existing schemes for selfish misbehavior detection depend on heuristic parameter configuration and experimental performance evaluation, we develop a Markov chain-based analytical model to systematically study the performance of the FS detector in real-time backoff misbehavior detection. Based on the analytical model, we can quantitatively compute the system configuration parameters for guaranteed performance in terms of average false positive rate, average detection delay, and missed detection ratio under a detection delay constraint. We present thorough simulation results to confirm the accuracy of our theoretical analysis as well as demonstrate the performance of the developed FS detector.
Index Terms:
Detectors,IEEE 802.11 Standards,Markov processes,Protocols,Delay,Analytical models,Real-time systems,CUSUM test,Detectors,IEEE 802.11 Standards,Markov processes,Protocols,Delay,Analytical models,Real-time systems,Markov chain model,Selfish misbehavior,real-time detection,IEEE 802.11
Citation:
Jin Tang, Yu Cheng, Weihua Zhuang, "Real-Time Misbehavior Detection in IEEE 802.11-Based Wireless Networks: An Analytical Approach," IEEE Transactions on Mobile Computing, vol. 13, no. 1, pp. 146-158, Jan. 2014, doi:10.1109/TMC.2012.227
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