An Evolutionary Approach for Learning Attack Specifications in Network Graphs

This paper presents an evolutionary algorithm that learns attack scenarios, called attack specifications, from a network graph. This learning process aims to find attack specifications that minimise cost and maximise the value that an attacker gets from a successful attack. The attack specifications that the algorithm learns are represented us-ing an approach based on Hoare’s CSP (Communicating Sequential Processes). This new approach is able to repre-sent several elements found in attacks, for example synchro-nisation. These attack specifications can be used by network administrators to find vulnerable scenarios, composed from the basic constructs Sequence, Parallel and Choice, that lead to valuable assets in the network