Analysis of Attack Graph Representations for Ranking Vulnerability Fixes

Tom Gonda, Tal Pascal, Rami Puzis, Guy Shani, Bracha Shapira

Research output: Contribution to conferencePaperpeer-review

Abstract

Software vulnerabilities in organizational computer networks can be leveraged by an attacker to gain access to sensitive information. As fixing all vulnerabilities requires much effort, it is critical to rank the possible fixes by their importance. Centrality measures over logical attack graphs, or over the network connectivity graph, often provide a scalable method for finding the most critical vulnerabilities. In this paper we suggest an analysis of the planning graph, originating in classical planning, as an alternative for the logical attack graph, to improve the ranking produced by centrality measures. The planning graph also allows us to enumerate the set of possible attack plans, and hence, directly count the number of attacks that use a given vulnerability. We evaluate a set of centrality-based ranking measures over the logical attack graph and the planning graph, showing that metrics computed over the planning graph reduce more rapidly the set of shortest attack plans.
Original languageAmerican English
DOIs
StatePublished - 17 Sep 2018
EventThe 4th Global Conference on Artificial Intelligence (GCAI 2018) - , Luxembourg
Duration: 17 Sep 201819 Sep 2018
https://easychair.org/smart-program/LuxLogAI2018/GCAI-index.html

Conference

ConferenceThe 4th Global Conference on Artificial Intelligence (GCAI 2018)
Country/TerritoryLuxembourg
Period17/09/1819/09/18
Internet address

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