Attack-defence trees are a promising approach for representing threat scenarios and possible countermeasures in a concise and intuitive manner. An attack-defence tree describes the interaction between an attacker and a defender, and is evaluated by assigning parameters to the nodes, such as probability or cost of attacks and defences. In case of multiple parameters most analytical methods optimise one parameter at a time, e.g., minimise cost or maximise probability of an attack. Such methods may lead to sub-optimal solutions when optimising conflicting parameters, e.g., minimising cost while maximising probability.In order to tackle this challenge, we devise automated techniques that optimise all parameters at once. Moreover, in the case of conflicting parameters our techniques compute the set of all optimal solutions, defined in terms of Pareto efficiency. The developments are carried out on a new and general formalism for attack-defence trees.

Abstract-Attack-defence trees are a powerful technique for formally evaluating attack-defence scenarios. They represent in an intuitive, graphical way the interaction between an attacker and a defender who compete in order to achieve conflicting objectives. We propose a novel framework for the formal analysis of quantitative properties of complex attack-defence scenarios, using an extension of attack-defence trees which models temporal ordering of actions and allows explicit dependencies in the strategies adopted by attackers and defenders. We adopt a game-theoretic approach, translating attack-defence trees to two-player stochastic games, and then employ probabilistic model checking techniques to formally analyse these models. This provides a means to both verify formally specified security properties of the attack-defence scenarios and, dually, to synthesise strategies for attackers or defenders which guarantee or optimise some quantitative property, such as the probability of a successful attack, the expected cost incurred, or some multi-objective trade-off between the two. We implement our approach, building upon the PRISM-games model checker, and apply it to a case study of an RFID goods management system.

No abstract

No abstract

Abstract. Attacks on organisations today explore many different layers, including buildings infrastructure, IT infrastructure, and human factor -the physical, virtual, and social layer. Identifying possible attacks, understanding their impact, and attributing their origin and contributing factors is difficult. Recently, system models have been used for automatically identifying possible attacks on the modelled organisation. The generated attacks consider all three layers, making the contribution of building infrastructure, computer infrastructure, and humans (insiders and outsiders) explicit. However, this contribution is only visible in the attack trees as part of the performed steps; it cannot be mapped back to the model directly since the actions usually involve several elements (attacker and targeted actor or asset). Especially for large attack trees, understanding the relations between several model components quickly results in a large quantity of interrelations, which are hard to grasp. In this work we present several approaches for visualising attributes of attacks such as likelihood of success, impact, and required time or skill level. The resulting visualisations provide a link between attacks on an organisations and the contribution of parts of an organisation to the attack and its impact.