Secure Non-Consensus Based Spectrum Sensing in Non-Centralized Cognitive Radio Networks

Abstract

In a non-centralized cognitive radio network, secondary users (SUs) cooperate in order to determine the presence of the primary user (PU) signal. This can be accomplished by each node sharing its spectrum sensing result with its neighboring SUs. In this paper, a non-consensus based distributed spectrum sensing (NCSS) scheme is presented, in which a node uses the raw energy level of the PU signal from its $h$ -hop neighbors for determining the status of the PU. A message passing scheme is used rather than the conventional consensus scheme. A comparison with an existing consensus algorithm is also shown. Further, two types of spectrum sensing data falsification attacks are considered in which the attackers inject very high or very low energy values. To catch such abnormal behavior of a node, an approach called secure NCSS algorithm is proposed, which isolates a node that generates extreme energy values so that it is removed from future computation. For this, an outlier detection technique is adopted. The approach is based on the idea that a malicious node’s energy level deviates significantly from those of genuine nodes, whereas all genuine nodes share nearby estimated energy levels.