What is Dempster-Shafer's model?
Advances in the Dempster-Shafer theory of evidence
Time, clocks, and the ordering of events in a distributed system
Communications of the ACM
Alert aggregation in mobile ad hoc networks
WiSe '03 Proceedings of the 2nd ACM workshop on Wireless security
Mobile-agent-based collaborative sensor fusion
Information Fusion
Blue force tracking network modeling and simulation
MILCOM'06 Proceedings of the 2006 IEEE conference on Military communications
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Limited capabilities and mission requirements imply that nodes in Tactical Mobile Ad-hoc NETworks (MANETs) carry a significant risk of being compromised physically or logically. In addition nodes or groups of nodes may defect, which is a particular concern in coalition environments where networks may spread beyond organizational boundaries. To identify defecting or compromised nodes including Byzantine behavior we propose a clustered intrusion detection architecture. Our architecture exploits multisensor data and supplementary information to identify defectors based on deviations from predicted values and correlated measurements and behavior. Furthermore multi-hop communication complexity is minimized to ensure robustness in environments with limited connectivity and frequent network partitioning. We show that our approach improves accuracy over naive Markov Chain and Kullback-Leibler divergence by boosting the number of particles, where probability density functions are highly nonlinear but partially known and can be determined using predictive importance sampling.