  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.
