Verifying Security Properties in Unbounded Multiagent Systems

We study the problem of analysing the security for an unbounded number of concurrent sessions of a cryptographic protocol. Our formal model accounts for an arbitrary number of agents involved in a protocol-exchange which is subverted by a Dolev-Yao attacker. We define the parameterised model checking problem with respect to security requirements expressed in temporal-epistemic logics. We formulate sufficient conditions for solving this problem, by analysing several finite models of the system. We primarily explore authentication and key-establishment as part of a larger class of protocols and security requirements amenable to our methodology. We introduce a tool implementing the technique, and we validate it by verifying the NSPK and ASRPC protocols

Proof Theory, Transformations, and Logic Programming for Debugging Security Protocols

We define a sequent calculus to formally specify, simulate, debug and verify security protocols. In our sequents we distinguish between the current knowledge of principals and the current global state of the session. Hereby, we can describe the operational semantics of principals and of an intruder in a simple and modular way. Furthermore, using proof theoretic tools like the analysis of permutability of rules, we are able to find efficient proof strategies that we prove complete for special classes of security protocols including Needham-Schroeder. Based on the results of this preliminary analysis, we have implemented a Prolog meta-interpreter which allows for rapid prototyping and for checking safety properties of security protocols, and we have applied it for finding error traces and proving correctness of practical examples

Parameterised model checking of probabilistic multi-agent systems

Swarm robotics has been put forward as a method of addressing a number of scenarios where scalability and robustness are desired. In order to deploy robotic swarms in safety-critical situations, it is necessary to verify their behaviour. Model checking gives a possible approach to do this; however, with traditional model checking techniques only systems of a finite size can be considered. This presents an issue for swarm systems, where the number of participants in the system is not known at design-time and may be arbitrarily large. To overcome this, parameterised model checking (PMC) techniques have been developed which enable the verification of systems where the number of participants is not known until run-time. However, protocols followed by robotic swarms are often stochastic in nature, and this cannot be modelled with current PMC techniques. This is the gap that this thesis aims to overcome. In particular, two parameterised semantics for reasoning about multi-agent systems are extended to incorporate probabilities. One of these semantics is synchronous, whilst the other is interleaved. Abstract models which overapproximate the systems being considered are constructed using counter abstraction techniques. These abstract models are used to develop parameterised verification procedures for a number of specification logics on both bounded and unbounded traces. The decision procedures presented are shown to be sound, and in some cases also complete. Further, the techniques are extended to allow modelling of situations where agents may exhibit faulty behaviour, as well as scenarios where the strategic capabilities of the participants needs to be verified. The procedures are all implemented in a novel verification toolkit called PSV (Probabilistic Swarm Verifier), built on top of the probabilistic model checker PRISM. This toolkit is used to verify three case studies from both swarm robotics and other application domains.Open Acces

A counter abstraction technique for the verification of robot swarms.

We study parameterised verification of robot swarms against temporal-epistemic specifications. We relax some of the significant restrictions assumed in the literature and present a counter abstraction approach that enable us to verify a potentially much smaller abstract model when checking a formula on a swarm of any size. We present an implementation and discuss experimental results obtained for the alpha algorithm for robot swarms