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arXiv research

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2 results for SIEM

Deep Belief Network reduces false positives in risky host detection.

problem Overwhelming alerts from SIEM systems, focusing on reducing false positives.
method Combines alert information, logs, and analyst results; uses text mining and graph-based methods for feature generation; compares against various machine learning algorithms.
result Deep Belief Network outperforms other algorithms, improving detection by six times.

Attack graphs provide compact representations of the attack paths that an attacker can follow to compromise network resources by analysing network vulnerabilities and topology. These representations are a powerful tool for security risk assessment. Bayesian inference on attack graphs enables the estimation of the risk …

2016-06-22abs ↗pdf ↗