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InfoResearchPeer-reviewed
Large-Scale Intranet Security Assessment Based on Bayesian Attack Graphs Using System Audit Logs
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Summary
This paper proposes a Bayesian attack graph method for large-scale, active intranet security assessment. It extracts system audit logs to capture real-time changes, generates attack graphs with MulVAL, and removes weak dependencies to find direct-risk paths. Tested on an enterprise intranet using logs from over 1,000 hosts, it reports intranet risk values at any given time and identifies specific, observable potential attack paths.