ACM Transactions on Information and System Security (TISSEC)
Mathematical Techniques in Multisensor Data Fusion
Mathematical Techniques in Multisensor Data Fusion
Learning nonstationary models of normal network traffic for detecting novel attacks
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Results of the KDD'99 classifier learning
ACM SIGKDD Explorations Newsletter
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Fusion of multiple intrusion detection systems results in a more reliable and accurate detection for a wider class of intrusions. The paper presented here introduces the mathematical basis for sensor fusion and provides enough support for the acceptability of sensor fusion in performance enhancement of intrusion detection systems. The sensor fusion system is characterized and modeled with no knowledge of the intrusion detection systems and the intrusion detection data. The theoretical analysis is supported with an experimental illustration with three of the available intrusion detection systems using the DARPA 1999 evaluation data set.