Formal Template-Based Generation of Attack–Defence Trees for Automated Security Analysis

Systems that integrate cyber and physical aspects to create cyber-physical systems (CPS) are becoming increasingly complex, but demonstrating the security of CPS is hard and security is frequently compromised. These compromises can lead to safety failures, putting lives at risk. Attack Defense Trees with sequential conjunction (ADS) are an approach to identifying attacks on a system and identifying the interaction between attacks and the defenses that are present within the CPS. We present a semantic model for ADS and propose a methodology for generating ADS automatically. The methodology takes as input a CPS system model and a library of templates of attacks and defenses. We demonstrate and validate the effectiveness of the ADS generation methodology using an example from the automotive domain

Modelling Socio-Technical Aspects of Organisational Security

Identification of threats to organisations and risk assessment often take into consideration the pure technical aspects, overlooking the vulnerabilities originating from attacks on a social level, for example social engineering, and abstracting away the physical infrastructure. However, attacks on organisations are far from being purely technical. After all, organisations consist of employees. Often the human factor appears to be the weakest point in the security of organisations. It may be easier to break through a system using a social engineering attack rather than a pure technological one. The StuxNet attack is only one of the many examples showing that vulnerabilities of organisations are increasingly exploited on different levels including the human factor. There is an urgent need for integration between the technical and social aspects of systems in assessing their security. Such an integration would close this gap, however, it would also result in complicating the formal treatment and automatic identification of attacks. This dissertation shows that applying a system modelling approach to sociotechnical systems can be used for identifying attacks on organisations, which exploit various levels of the vulnerabilities of the systems. In support of this claim we present a modelling framework, which combines many features. Based on a graph, the framework presents the physical infrastructure of an organisation, where actors and data are modelled as nodes in this graph. Based on the semantics of the underlying process calculus, we develop a formal analytical approach that generates attack trees from the model. The overall goal of the framework is to predict, prioritise and minimise the vulnerabilities in organisations by prohibiting the overall attack or at least increasing the difficulty and cost of fulfilling it. We validate our approach using scenarios from IPTV and Cloud Infrastructure case studies

Risk Monitoring and Intrusion Detection for Industrial Control Systems

Cyber-attacks on critical infrastructure such as electricity, gas, and water distribution, or power plants, are more and more considered to be a relevant and realistic threat to the European society. Whereas mature solutions like anti-malware applications, intrusion detection systems (IDS) and even intrusion prevention or self-healing systems have been designed for classic computer systems, these techniques have only been partially adapted to the world of Industrial Control Systems (ICS). As a consequence, organisations and nations fall back upon risk management to understand the risks that they are facing. Today's trend is to combine risk management with real-time monitoring to enable prompt reactions in case of attacks. This thesis aims at providing techniques that assist security managers in migrating from a static risk analysis to a real-time and dynamic risk monitoring platform. Risk monitoring encompasses three steps, each being addressed in detail in this thesis: the collection of risk-related information, the reporting of security events, and finally the inclusion of this real-time information into a risk analysis. The first step consists in designing agents that detect incidents in the system. In this thesis, an intrusion detection system is developed to this end, which focuses on an advanced persistent threat (APT) that particularly targets critical infrastructures. The second step copes with the translation of the obtained technical information in more abstract notions of risk, which can then be used in the context of a risk analysis. In the final step, the information collected from the various sources is correlated so as to obtain the risk faced by the entire system. Since industrial environments are characterised by many interdependencies, a dependency model is elaborated which takes dependencies into account when the risk is estimated