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.
A bayesian network model for predicting cyber security threats,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CR 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
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.