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Consensus algorithms provide strategies to solve problems in a distributedsystem with the added constraint that data can only be shared between adjacentcomputing nodes. We find these algorithms in applications for wireless andsensor networks, spectrum sensing for cognitive radio, even for some IoTservices. However, consensus-based applications are not resilient tocompromised nodes sending falsified data to their neighbors, i.e. they can bethe target of Byzantine attacks. Several solutions have been proposed in theliterature inspired from reputation based systems, outlier detection ormodel-based fault detection techniques in process control. We have reviewedsome of these solutions, and propose two mitigation techniques to protect theconsensus-based Network Intrusion Detection System in\cite{toulouse2015consensus}. We analyze several implementation issues such ascomputational overhead, fine tuning of the solution parameters, impacts on theconvergence of the consensus phase, accuracy of the intrusion detection system.

Robust Consensus-Based Network Intrusion Detection in Presence of Byzantine Attacks