Logic and information
Original Contribution: Stacked generalization
Neural Networks
Combining classifiers using correspondence analysis
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Arbitrating among competing classifiers using learned referees
Knowledge and Information Systems
Network Intrusion Detection: An Analyst's Handbook
Network Intrusion Detection: An Analyst's Handbook
Hacking Exposed Windows 2000: Network Security Secrets and Solutions
Hacking Exposed Windows 2000: Network Security Secrets and Solutions
Hacking Exposed
Multi-agent Technology for Distributed Data Mining and Classification
IAT '03 Proceedings of the IEEE/WIC International Conference on Intelligent Agent Technology
Multi-agent system development kit: MAS software tool implementing Gaia methodology
Intelligent information processing II
Infrastructural Issues for Agent-Based Distributed Learning
WI-IATW '06 Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology
Proceedings of the 2008 conference on Formal Ontologies Meet Industry
Asynchronous alert correlation in multi-agent intrusion detection systems
MMM-ACNS'05 Proceedings of the Third international conference on Mathematical Methods, Models, and Architectures for Computer Network Security
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Situation is an abstraction that characterizes a complex system consisting of semi-autonomous objects striving to achieve certain particular goals (sequences of goals) and operating in a coordinated mode controlled by a meta-goal of the system on the whole. Situation and objects are discriminated by their "states" taking values from finite sets of classes' labels. Situation assessment, which is the topmost task in many practically important applications, is a classification task aimed at assessing the situation current state and assigning a class label to the situation. The paper covers certain key issues of the situation assessment problem. It analyses formal frameworks proposed for specification of the situation models, and highlights a number of challenging problems associated with situation assessment, the most crucial of which is caused by the peculiarities of input data used for situation assessment, which are a superposition of asynchronous discrete streams of heterogeneous data received from multiple sources and having finite "life time". The paper is focused on the approaches and algorithms intended for on-line updating of the situation assessment, on the situation assessment systems generic architecture and on the demonstration of the proposed techniques and architecture using a computer assurance system solving anomaly detection task.