Path problems in networks with vector-valued edge weights

Tayi, Giri Kumar; Rosenkrantz, Daniel J.; Ravi, S. S.

doi:10.1002/(sici)1097-0037(199908)34:1<19::aid-net3>3.0.co;2-6

Cited by 6 publications

(1 citation statement)

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“…However, scaling provides a graceful tradeoff between approximation quality and the time and space needed to compute the solution [15]. Very recently, Tayi et al [18] have shown how to compute all undominated (Pareto optimal) paths for multiple edge weights. Their algorithm runs in pseudo-polynomial time provided the number of criteria is bounded (i.e., the exponent in the running time depends on the number of criteria).…”

Section: Analysis Methodsmentioning

confidence: 99%

A graph-based system for network-vulnerability analysis

Phillips

Swiler

1998

Proceedings of the 1998 Workshop on New Security Paradigms

605

387

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O S T I This paper presents a graph-based approach to network vulnerability analysis. The method is flexible, allowing analysis of attacks from both outside and inside the network. It can analyze risks to a specific network asset, or examine the universe of possible consequences following a successful attack. The graph-based tool can identify the set of attack paths that have a high probability of success (or a low "effort" cost) for the attacker. The system could be used to test the effectiveness of making configuration changes, implementing an intrusion detection system, etc. The analysis system requires as input a database of common attacks, broken into atomic steps, specific network configuration and topology information, and an attacker profile. The attack information is "matched" with the network configuration information and an attacker profile to create a superset attack graph. Nodes identify a stage of attack, for example the class of machines the attacker has accessed and the user privilege level he or she has compromised. The arcs in the attack graph represent attacks or stages of attacks. By assigning probabilities of success on the arcs or costs representing level-of-effort for the attacker, various graph algorithms such as shortest-path algorithms can identify the attack paths with the highest probability of success.

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Section: Analysis Methodsmentioning

confidence: 99%