Abstract
Cognitive radio (CR) is being considered as a vital technology to provide solution to spectrum scarcity in next generation network, by efficiently utilizing the vacant spectrum of the licensed users. Cooperative spectrum sensing in cognitive radio network has a promising performance compared to the individual sensing. However, the existence of the malicious users’ attack highly degrades the performance of the cognitive radio networks by sending falsified data also known as spectrum sensing data falsification (SSDF) to the fusion center. In this paper, we propose a double adaptive thresholding technique in order to differentiate legitimate users from doubtful and malicious users. Prior to the double adaptive approach, the maximal ratio combining (MRC) scheme is utilized to assign weight to each user such that the legitimate users experience higher weights than the malicious users. Double adaptive threshold is applied to give a fair chance to the doubtful users to ensure their credibility. A doubtful user that fails the double adaptive threshold test is declared as a malicious user. The results of the legitimate users are combined at the fusion center by utilizing Dempster-Shafer (DS) evidence theory. Effectiveness of the proposed scheme is proved through simulations by comparing with the existing schemes.
Highlights
Wireless network technologies are the most promising technologies in the twentieth century
The spectrum sensing data falsification attacks falsifies the sensing results, which highly degrades the performance of cooperative spectrum sensing
We proposed a double adaptive approach in cognitive radio networks to deal with legitimate, doubtful, and malicious users in the ROC for "Always No" attack 1
Summary
Wireless network technologies are the most promising technologies in the twentieth century. Energy detector is a noncoherent detector which detects the presence of the LU signal by measuring its energy and comparing it with a predetermined threshold This technique does not require any prior information about LU and it is easy to implement and to be extended for the other spectrum sensing. In [9], a scheme was proposed to prevent the SSDF attacks by calculating and updating the credit value of the SUs; malicious users are excluded to avoid the SSDF attacks in cooperative spectrum sensing. We utilize D-S evidence theory with double adaptive threshold method to differentiate among legitimate, doubtful, and malicious users.
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