Alessandro Bruni

Alexandros Bampoulidis, Alessandro Bruni, Lukas Helminger et al.

Recent work has shown that cell phone mobility data has the unique potential to create accurate models for human mobility and consequently the spread of infected diseases. While prior studies have exclusively relied on a mobile network operator's subscribers' aggregated data in modelling disease dynamics, it may be preferable to contemplate aggregated mobility data of infected individuals only. Clearly, naively linking mobile phone data with health records would violate privacy by either allowing to track mobility patterns of infected individuals, leak information on who is infected, or both. This work aims to develop a solution that reports the aggregated mobile phone location data of infected individuals while still maintaining compliance with privacy expectations. To achieve privacy, we use homomorphic encryption, validation techniques derived from zero-knowledge proofs, and differential privacy. Our protocol's open-source implementation can process eight million subscribers in 70 minutes.

Matthew L. Daggit, Alistair Sirman, Alessandro Bruni et al.

Formal verification of neuro-symbolic cyber-physical systems, such as drones, medical devices and robots, is complicated. Neural components must be trained to be optimal with respect to the available data as well as the safety specifications, and then verified using specialised solvers. Symbolic models of the "cyber" and "physical" behaviour of the system must be constructed and verified in interactive theorem provers (ITPs), often requiring mature mathematical libraries to reason about the interplay of discrete and continuous dynamics, preferably obtaining infinite time-horizon guarantees. Finally, the results of the two already challenging verification tasks need to be integrated into a single proof in a coherent and consistent way, whilst preserving deployability of the resulting model. In this paper we present a compositional methodology for constructing such proofs. The Vehicle framework provides a functional, domain-specific language for specifying, training, and verifying neural components. We extend Vehicle to allow integration with any ITP with minimal effort. First, we describe how Vehicle's standard bidirectional type checker can be reused to transpile neural specifications into an intermediate representation targeting multiple theorem provers. Second, we integrate Vehicle with Rocq, Isabelle/HOL, Agda and the industrial prover Imandra; and showcase a generic infinite time-horizon safety proof of a discrete cyber-physical system with a neural network controller in each ITP. Finally, we use the Mathematical Components libraries in Rocq to verify infinite time-horizon safety of a medical device, modelled as a continuous cyber-physical system with a neural controller. To our knowledge, this is the first result of this kind in a general purpose ITP; and a result that was only feasible thanks to the compositionality provided by Vehicle's functional interface.

Karl Norrman, Vaishnavi Sundararajan, Alessandro Bruni

Constrained IoT devices are becoming ubiquitous in society and there is a need for secure communication protocols that respect the constraints under which these devices operate. EDHOC is an authenticated key establishment protocol for constrained IoT devices, currently being standardized by the Internet Engineering Task Force (IETF). A rudimentary version of EDHOC with only two key establishment methods was formally analyzed in 2018. Since then, the protocol has evolved significantly and several new key establishment methods have been added. In this paper, we present a formal analysis of all EDHOC methods in an enhanced symbolic Dolev-Yao model using the Tamarin tool. We show that not all methods satisfy the authentication notion injective of agreement, but that they all do satisfy a notion of implicit authentication, as well as Perfect Forward Secrecy (PFS) of the session key material. We identify other weaknesses to which we propose improvements. For example, a party may intend to establish a session key with a certain peer, but end up establishing it with another, trusted but compromised, peer. We communicated our findings and proposals to the IETF, which has incorporated some of these in newer versions of the standard.