A Confidence-Aware Trust Approach for Detecting Indirect Sybil Attacks in Wireless Sensor Networks Considering Time Factor

Wireless Sensor Networks (WSNs) gather the environmental information via some sensor nodes and send them after some simple processing functions if necessary. These nodes are constrained devices in terms of memory, processing capability, radio range, and energy. Due to the unattended deployment of sensor nodes and the nature of wireless communications, these networks are vulnerable to several attacks. Among these, the Sybil Attack is a serious threat in which a malicious node creates multiple fake identities in order to mislead the other sensor nodes. In this case, the malicious node can attract lots of traffic and disrupt routing protocols. In this paper, we present a confidence-aware trust model considering Time Factor to detect such attacks. In this model, we use the indirect trust, gained from the neighbor's recommendations, in order to detect the indirect Sybil attacks, in which a legal node is not directly associated with the Sybil node. The Algorithm has been implemented using MATLAB. The simulation results demonstrate significant preference of the proposed method in terms of detection accuracy and false alarm rates. The average rate of detection and false detection of the proposed model are 93% and 0.26%.