On the Greedy Resource Occupancy Threat in Dynamic Spectrum Access

• Published in: IEEE transactions on vehicular technology Vol. 66; no. 12; pp. 11233 - 11248
• Main Authors: Ma, Songjun, Liu, Xiao-Yang, Fu, Luoyi, Tian, Xiaohua, Gan, Xiaoying, Wang, Xinbing
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.12.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cognitive radio; Computer simulation; Dynamic spectrum access; Economics; Emulation; greedy behavior; Occupancy; Performance degradation; protection; Queueing analysis; Queues; Queuing theory; Security; Sensors; Strategy; System performance; threat detection; Wavelet analysis
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2017.2722409

Recently, security issues in dynamic spectrum access (DSA) received more and more attention. One type of threat, which we call the greedy resource occupancy, has long been ignored so far. Specifically, a secondary user (SU) may greedily occupy spectrum for a long time, which makes other SUs suffer additional waiting time to access the spectrum and leads to congestion or breakdown. In this paper, we investigated the DSA networks with greedy users. The primary user's privilege of accessing the networks at any time is also taken into account. Accordingly, the process of DSA is treated as a privilege-existing multidimensional queueing process. First, we propose an analysis framework for the queueing system and exploit it to investigate impacts of greedy SUs (GSUs) on system performance, i.e., the queue size and waiting time in queue. Second, we propose a wavelet based method to detect the greedy resource occupancy threat quickly. Since a sudden change in average occupancy time of the GSU will produce dramatic performance degradation, the GSU prefers to increase his occupancy time in a gradual manner to avoid the easy detection. Third, to protect honest SUs from being affected by GSUs, a protection strategy is put forward, and the system performance with the strategy has also been analyzed by the queueing analysis. Last, we conduct numerical analyses to demonstrate explicit impacts of GSUs on the system performance as well as efficacy of the protection strategy. We also carry out simulations on the detecting approach, and the results verify effectiveness and efficiency of our proposed approach.