Fairness is a desirable and crucial property of many protocols that handle, for instance, exchanges of message. It states that if at least one agent engaging in the protocol is honest, then either the protocol will unfold correctly and fulfill its intended goal for all participants, or it will fail for everyone. In this work, we present a game-based framework for the study of fairness protocols, that does not define a priori an attacker model. It is based on the notion of strong secure equilibria, and leverages the conceptual and algorithmic toolbox of game theory. In the case of finite games, we provide decision procedures with tight complexity bounds for determining whether a protocol is immune to nefarious attacks from a coalition of participants, and whether such a protocol could exist based on the underlying graph structure and objectives.

In this article, we propose to use game theory to model our WSN network. In this setting, the goal of the compromised node is to keep disrupting the network while remaining alive. The game studied is a two-player quantitative infinite game on a finite graph, where each transition can change some energy levels and some reward. The goal of the compromised node is hence to maximize its reward while maintaining a positive energy level. On the theoretical side, we show that solving these games is not algorithmically possible if the objective is too complex. We can however provide solutions in some restricted cases. The ultimate purpose is to demonstrate that, with the presented detection solution, a compromised node cannot “win the game”, and hence either gets detected, dies, or behaves as an normal (sane) node would.

Opacity is a general language-theoretic framework in which several security properties of a system can be expressed. Its parameters are a predicate, given as a subset of runs of the system, and an observation function, from the set of runs into a set of observables. The predicate describes secret information in the system and, in the possibilistic setting, it is opaque if its membership cannot be inferred from observation. In this paper, we propose several notions of quantitative opacity for probabilistic systems, where the predicate and the observation function are seen as random variables. Our aim is to measure (i) the probability of opacity leakage relative to these random variables and (ii) the level of uncertainty about membership of the predicate inferred from observation. We show how these measures extend possibilistic opacity, we give algorithms to compute them for regular secrets and observations, and we apply these computations on several classical examples. We finally partially investigate the non-deterministic setting.

Interrupt Timed Automata (ITA) have been introduced to model multi-task systems with interruptions. They form a subclass of stopwatch automata, where the real valued variables (with rate 0 or 1) are organized along priority levels. While reachability is undecidable with usual stopwatches, the problem was proved decidable for ITA. In this work, after giving answers to some questions left open about expressiveness, closure, and complexity for ITA, our main purpose is to investigate the verification of real time properties over ITA. While we prove that model checking a variant of the timed logic TCTL is undecidable, we nevertheless give model checking procedures for two relevant fragments of this logic: one where formulas contain only model clocks and another one where formulas have a single external clock.