学术文献库

Designing security systems for wireless sensor networks presents a challenge due to their relatively low computational resources. This has rendered many traditional defense mechanisms based on cryptography infeasible for deployment on such networks. Reputation and anomaly detection systems have been implemented as viable alternatives, but existing implementations still struggle with providing efficient security without a significant impact on energy consumption. To address this trade-off between resource consumption and resiliency, we designed TrustSense, a reputation management protocol for clustered WSNs. It is a semi-centralized family of algorithms that combine periodic trust updates, spatial correlation, and packet sequence validation at the cluster-heads' hierarchy to relieve the sensor nodes of unnecessary opinion queries and trust evaluation computation. We compared the efficiency of TrustSense with legacy reputation systems such as EigenTrust and the results of simulations show a significant improvement in reliability and energy usage while maintaining an acceptable path length with varying numbers of malicious nodes. We believe the approach of combining different techniques from various classes of intrusion detection systems unlocks several possibilities of achieving better results by more complex and versatile composition of these techniques.