Node replication attack detection strategy integrating node creditworthiness and identity authentication

Abstract:

To defend against node replication attacks in wireless sensor networks and maintain network security and stability, this paper proposes a node replication attack detection strategy integrating node creditworthiness and identity authentication (NRADS-NC＆IA). The approach begins by establishing a fuzzy comprehensive trust evaluation model. In the direct trust module, reputation maintenance function, anomaly attenuation factor and reward and punishment factor are introduced. The direct trust value of the node to be evaluated is calculated by comprehensively considering the influencing factors of communication attributes, data attributes, network attributes and physical attributes. A sliding time window mechanism is adopted to dynamically update node trust value, significantly enhancing the timeliness and accuracy of the evaluation. On this basis, a support function is applied to evaluate the credibility of nodes, effectively filtering out the deceptive behaviors of nodes and obtaining more reliable indirect trust values of nodes. The final comprehensive trust value of nodes is derived from the weighted summation of its direct and indirect trust values. Dynamic adaptive thresholds are adopted to screen suspicious nodes, and node ID comparisons are conducted among the suspicious nodes to obtain the determined replica nodes. Simulation results show that NRADS-NC&IA achieves detection rates of over 97% and 94% in static and mobile wireless sensor networks without relying on the spatial position information of nodes. The strategy exhibits strong environmental adaptability and can effectively deal with the security problems of wireless sensor networks in complex dynamic environments.