Despite the increased focus on security, complex networked systems remain vulnerable to attacks. Intrusion Tolerance is an emerging paradigm for developing systems, which continue to operate correctly, and provide acceptable services even in the face of an intrusion. The effectiveness of this approach is strongly dependent on the efficiency of the adopted detection and diagnosis mechanisms. In this work, we propose an architectural framework, which collects information at several architectural levels, using multiple security probes, which are deployed as a distributed architecture, to perform event correlation and diagnosis analysis of intrusion symptoms. The experimental results show that the use of different security information sources can improve the detection and the diagnosis of attacks
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