A queueing framework segments vulnerability data with Gaussian mixture models, fits arrival/service/resource parameters by KL-divergence minimization, and reports 91-96% accuracy in estimating organizational cyber resources from timestamps.
Dynamic security risk manage- ment using bayesian attack graphs
3 Pith papers cite this work. Polarity classification is still indexing.
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cs.CR 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
Process mining on network traffic supplies evidence to update Bayesian Attack Graphs for dynamic assessment of active CVE exploitation and overall system risk.
A queueing model of attack surfaces validated on supply-chain data shows AI automation can raise exploit rates and an RL policy cuts active vulnerabilities by over 90% without extra budget.
citing papers explorer
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Organizational Security Resource Estimation via Vulnerability Queueing
A queueing framework segments vulnerability data with Gaussian mixture models, fits arrival/service/resource parameters by KL-divergence minimization, and reports 91-96% accuracy in estimating organizational cyber resources from timestamps.
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Dynamic Risk Assessment by Bayesian Attack Graphs and Process Mining
Process mining on network traffic supplies evidence to update Bayesian Attack Graphs for dynamic assessment of active CVE exploitation and overall system risk.
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A Queueing-Theoretic Framework for Dynamic Attack Surfaces: Data-Integrated Risk Analysis and Adaptive Defense
A queueing model of attack surfaces validated on supply-chain data shows AI automation can raise exploit rates and an RL policy cuts active vulnerabilities by over 90% without extra budget.