Privacy Architectures: Reasoning About Data Minimisation and Integrity

Privacy by design will become a legal obligation in the European Community if the Data Protection Regulation eventually gets adopted. However, taking into account privacy requirements in the design of a system is a challenging task. We propose an approach based on the specification of privacy architectures and focus on a key aspect of privacy, data minimisation, and its tension with integrity requirements. We illustrate our formal framework through a smart metering case study.Comment: appears in STM - 10th International Workshop on Security and Trust Management 8743 (2014

Metrics for Differential Privacy in Concurrent Systems

Part 3: Security AnalysisInternational audienceOriginally proposed for privacy protection in the context of statistical databases, differential privacy is now widely adopted in various models of computation. In this paper we investigate techniques for proving differential privacy in the context of concurrent systems. Our motivation stems from the work of Tschantz et al., who proposed a verification method based on proving the existence of a stratified family between states, that can track the privacy leakage, ensuring that it does not exceed a given leakage budget. We improve this technique by investigating a state property which is more permissive and still implies differential privacy. We consider two pseudometrics on probabilistic automata: The first one is essentially a reformulation of the notion proposed by Tschantz et al. The second one is a more liberal variant, relaxing the relation between them by integrating the notion of amortisation, which results into a more parsimonious use of the privacy budget. We show that the metrical closeness of automata guarantees the preservation of differential privacy, which makes the two metrics suitable for verification. Moreover we show that process combinators are non-expansive in this pseudometric framework. We apply the pseudometric framework to reason about the degree of differential privacy of protocols by the example of the Dining Cryptographers Protocol with biased coins

Generalized bisimulation metrics

International audienceThe pseudometric based on the Kantorovich lifting is one of the most popular notion of distance between probabilistic processes proposed in the literature. However, its application in verification is limited to linear properties. We propose a generalization which allows to deal with a wider class of properties, such as those used in security and privacy. More precisely, we propose a family of pseudometrics, parametrized on a notion of distance which depends on the property we want to verify. Furthermore, we show that the members of this family still characterize bisimilarity in terms of their kernel, and provide a bound on the corresponding distance between trace distributions. Finally, we study the instance corresponding to differential privacy, and we show that it has a dual form, easier to compute. We also prove that the typical process-algebra constructs are non-expansive, thus paving the way to a modular approach to verification

Privacy by Design: From Technologies to Architectures (Position Paper)

Existing work on privacy by design mostly focus on technologies rather than methodologies and on components rather than architectures. In this paper, we advocate the idea that privacy by design should also be addressed at the architectural level and be associated with suitable methodologies. Among other benefits, architectural descriptions enable a more systematic exploration of the design space. In addition, because privacy is intrinsically a complex notion that can be in tension with other requirements, we believe that formal methods should play a key role in this area. After presenting our position, we provide some hints on how our approach can turn into practice based on ongoing work on a privacy by design environment