Cooperative sensing in cognitive networks under malicious attack
This paper considers cooperative sensing in cognitive networks under Spectrum Sensing Data Falsification attack (SSDF) in which malicious users can intentionally send false sensing information. One effective method to deal with the SSDF attack is the q-out-of-m scheme, where the sensing decision is based on q sensing reports out of m polled nodes. The major limitation with the q-out-of-m scheme is its high computational complexity due to exhaustive search. In this paper, we prove that for a fixed percentage of malicious users, the detection accuracy increases almost exponentially as the network size increases. Motivated by this observation, as well as the linear relationship between the scheme parameters and the network size, we propose a simple but accurate approach that significantly reduces the complexity of the q-out-of-m scheme. The proposed approach can easily be applied to the large scale networks, which can be much more reliable under malicious attacks.