The maximum concurrent flow problem
Journal of the ACM (JACM)
Automated Generation and Analysis of Attack Graphs
SP '02 Proceedings of the 2002 IEEE Symposium on Security and Privacy
Expander flows, geometric embeddings and graph partitioning
STOC '04 Proceedings of the thirty-sixth annual ACM symposium on Theory of computing
MulVAL: a logic-based network security analyzer
SSYM'05 Proceedings of the 14th conference on USENIX Security Symposium - Volume 14
Using Software Dependencies and Churn Metrics to Predict Field Failures: An Empirical Case Study
ESEM '07 Proceedings of the First International Symposium on Empirical Software Engineering and Measurement
IEEE Transactions on Software Engineering
Proceedings of the ACM SIGOPS 22nd symposium on Operating systems principles
Expectation propagation for approximate Bayesian inference
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
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Motivated by applications from computer network security and software engineering, we study the problem of reducing reachability on a graph with unknown edge costs. When the costs are known, reachability reduction can be solved using a linear relaxation of sparsest cut. Problems arise, however, when edge costs are unknown. In this case, blindly applying sparsest cut with incorrect edge costs can result in suboptimal or infeasible solutions. Instead, we propose to solve the problem via edge classification using feedback on individual edges. We show that this approach outperforms competing approaches in accuracy and efficiency on our target applications.