ABSTRACT. We will discuss intrusion tolerance as a desirable property of cyber systems and discuss the relationship between intrusion tolerance and resilience. Intrusion-tolerant complex systems maintain certain security properties even when components of those systems are compromised. We will examine some ways to quantify intrusion tolerance using graphical models of complex cyber systems with a focus on the misuse of authentication credentials and the exploitation of trust relationships. Finally, we will provide some examples of the impact of this analysis on real-world policy decisions.

ABSTRACT. In the context of business process management, the implementation of data minimization requirements requires that analysts are able to assert what private data each worker is able to access, not only directly via the inputs of the tasks they perform in a business process, but also indirectly via the chain of tasks that lead to the production of these inputs. In this setting, this paper presents a technique which, given a workflow that transforms a set of input tables into a set of output tables via a set of inter-related SQL statements, determines what information from each input table is disclosed by each output table, and under what conditions this disclosure occurs. The result of this disclosure analysis is a summary representation of the possible computations leading from the inputs of the workflow to a given output thereof.

ABSTRACT. The risk from insider threats is rising significantly, yet the majority of organizations are ill-prepared to detect and mitigate them. Research has focused on providing rule-based detection systems or anomaly detection tools which use features indicative of malicious insider activity. In this paper we propose a system complimentary to the aforementioned approaches. Based on theoretical advances in describing attack patterns for insider activity, we design and validate a state-machine system that can effectively combine policies from rule-based systems and alerts from anomaly detection systems to create attack patterns that insiders follow to execute an attack. We validate the system in terms of effectiveness and scalability by applying it on ten synthetic scenarios. Our results show that the proposed system allows analysts to craft novel attack patterns and detect insider activity while requiring minimum computational time and memory.

ABSTRACT. Because of modern societies' dependence on industrial control systems, adequate response to system failures is essential. In order to take appropriate measures, it is crucial for operators to be able to distinguish between intentional attacks and accidental technical failures. However, adequate decision support for this matter is lacking. In this paper, we use Bayesian Networks (BNs) to distinguish between intentional attacks and accidental technical failures, based on contributory factors and observations (or test results). To facilitate knowledge elicitation, we use extended fishbone diagrams for discussions with experts, and then translate those into the BN formalism. We demonstrate the methodology using an example in a case study from the water management domain.

ABSTRACT. As cryptocurrencies enter the lives of the ordinary people cybercriminals start using them to facilitate crime. Europol last year estimated that about 3-4% of crime proceeds are laundered through the use of cryptocurrencies and that this figure is rising steadily. There are two main reasons - lack of regulation and anonymity. Recently, Anderson et al. showed that it is both computationally and legally possible to follow the 'taint' that a stolen coin leaves as it propagates through the network. In this paper we present new visualisation mechanisms for taint propagation in Bitcoin that display how cyber criminals launder money.

ABSTRACT. We define and study the decision problem of the \emph{emptiness} of an attack tree. This decision problem reflects the natural question of knowing whether some attack scenario described by the tree holds in a given model of the system to defend. We establish accurate complexity bounds, ranging from \NP-completeness for arbitrary trees down to \NLOGSPACE-completeness for trees with no occurrence of the \AND operator. Additionally, if the input system to defend has a succinct description, we show that the emptiness problem is \PSPACE-complete.

ABSTRACT. Attack trees provide a structure to an attack scenario, where disjunctions represent choices decomposing attacker's goals into smaller subgoals. This paper investigates the nature of choices in attack trees. For some choices, the attacker has the initiative, but for other choices either the environment or an active defender decides. A semantics for attack trees combining both types of choice is expressed in linear logic and connections with extensive-form games are highlighted. The linear logic semantics defines a specialisation preorder enabling trees, not necessarily equal, to be compared in such a way that all strategies are preserved.

ABSTRACT. This paper has two main contributions. The first is a new linear logical semantics of causal attack trees in four-valued truth tables. Our semantics is very simple and expressive, supporting specializations, and combines in an interesting way the ideal and filter semantics of causal attack trees. Our second contribution is Lina, a new embedded, in Haskell, domain specific functional programming language for conducting threat analysis using attack trees. Lina has many benefits over existing tools; for example, Lina allows one to specify attack trees very abstractly, which provides the ability to develop libraries of attack trees, furthermore, Lina is compositional, allowing one to break down complex attack trees into smaller ones that can be reasoned about and analyzed incrementally. Furthermore, Lina supports automatically proving properties of attack trees, such as equivalences and specializations, using Maude and the semantics introduced in this paper.