Dr Solofomampionona Fortunat Rajaona

We give a general-purpose programming language in which programs can reason about their own knowledge. To specify what these intelligent programs know, we define a " program epistemic " logic, akin to a dynamic epistemic logic for programs. Our logic properties are complex , including programs introspecting into future state of affairs, i.e., reasoning now about facts that hold only after they and other threads will execute. To model aspects anchored in privacy, our logic is interpreted over partial observability of variables, thus capturing that each thread can " see " only a part of the global space of variables. We verify program-epistemic properties on such AI-centred programs. To this end, we give a sound translation of the validity of our program-epistemic logic into first-order validity, using a new weakest-precondition semantics and a book-keeping of variable assignment. We implement our translation and fully automate our verification method for well-established examples using SMT solvers.

We propose a new approach to the verification of epis-temic properties of programs. First, we introduce the new " program-epistemic " logic L PK , which is strictly richer and more general than similar formalisms appearing in the literature. To solve the verification problem in an efficient way, we introduce a translation from our language L PK into first-order logic. Then, we show and prove correct a reduction from the model checking problem for program-epistemic formulas to the satisfiability of their first-order translation. Both our logic and our translation can handle richer specification w.r.t. the state of the art, allowing us to express the knowledge of agents about facts pertaining to programs (i.e., agents' knowledge before and after a program is executed). Furthermore, we implement our translation in Haskell in a general way (i.e., independently of the programs in the logical statements), and we use existing SMT-solvers to check satisfaction of L PK formulas on a benchmark example in the AI/agency field.

We introduce a new framework, TrackDev, for encoding and analysing the tracing or "tracking" of an entity (e.g., a device) via its executions of a protocol or its usages of a system. TrackDev considers multiple dimensions combined: whether the attacker is active or passive, whether an entity is trackable in its every single appearances or just in a compound set thereof, and whether the entity can be explicitly or implicitly identified. TrackDev can be applied to most identification-based systems. TrackDev is to be applied in practice, over actual executions of systems; to this end, we test TrackDev on real-life traffic for two well-known protocols, the LoRaWAN Join and the 5G handovers, showing new trackability attacks therein and proposing countermeasures. We study the strength of TrackDev's various trackability properties and show that many of our notions are incomparable amongst each other, thus justifying the fine-grained nature of TrackDev. Finally, we detail how the main thrust of TrackDev can be mechanised in formal-verification tools, without any loss; we exemplify this fully on the LoRaWAN Join, in the Tamarin prover. In this process, we also uncover and discuss within two important aspects: (a) TrackDev’s separation between "explicit" and "implicit" trackability offers new formal-verification insights; (b) our analyses of the LoRaWAN Join protocol in Tamarin against TrackDev as well as against existing approximations of unlinkability by Baelde et al. concretely show that the latter approximations can be coarser than our notions.