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- W2029425905 abstract "Novel methods of detecting cyber attacks on networks have been developed that are able to detect an increasing diverse variety of malicious cyber-events. However, this has only resulted in additional information burden on the network analyst. The integration of the distributed evidence from multiple sources is missing or ad-hoc at best. Only with the fusion of the multi-source evidence can we reason at a higher semantic level to detect and identify attacks and attackers. Further, integration at a higher semantic level will reduce the cognitive load on the security offcer and will make it possible for reasonable responses. This paper presents an overview of the D-Force system that uses a Bayesian Evidential Framework for fusing the multi-source evidence in a network to detect and recognize attacks. Attack hypothesis are generated as a result of evidence at the different network and host sensors. The hypotheses are verified or denied with additional evidence. Based on our initial experiments and tests the D-Force system promises to be a powerful tool in the information security offcers arsenal." @default.
- W2029425905 created "2016-06-24" @default.
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- W2029425905 date "2006-04-17" @default.
- W2029425905 modified "2023-09-23" @default.
- W2029425905 title "Multisource evidence fusion for cyber-situation assessment" @default.
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- W2029425905 doi "https://doi.org/10.1117/12.663436" @default.
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