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Collaborative systems research in the last decade have led to the development in several areas ranging from social computing, e-learning systems to management of complex computer networks. Intrusion Detection Systems (IDS) available today have a number of problems that limit their configurability, scalability or efficiency. An important shortcoming is that the existing architectures is built around a single entity that does most of the data collection and analysis. This work introduces a new architecture for intrusion detection and prevention based on multiple autonomous agents working collectively. We adopt a temporal logic approach to signature-based intrusion detection. We specify intrusion patterns as formulas in a monitorable logic called EAGLE. We also incorporate logics of knowledge into the agents. We implement a prototype tool, called MIDTL and use this tool to detect a variety of security attacks in large log-files provided by DARPA.
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Das et al. (2011) studied this question.
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