Overall Objectives
Research Program
Application Domains
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
XML PDF e-pub
PDF e-Pub

Section: New Results

Software Composition

Participants : Walid Benghrabit, Ronan-Alexandre Cherrueau, Rémi Douence, Hervé Grall, Jean-Claude Royer, Mario Südholt.

Constructive Security

Nowadays we are witnessing the wide-spread use of cloud services. As a result, more and more end-users (individuals and businesses) are using these services for achieving their electronic transactions (shopping, administrative procedures, B2B transactions, etc.). In such scenarios, personal data is generally flowing between several entities and end-users need (i) to be aware of the management, processing, storage and retention of personal data, and (ii) to have necessary means to hold service providers accountable for the usage of their data. Usual preventive security mechanisms are not adequate in a world where personal data can be exchanged on-line between different parties and/or stored at multiple jurisdictions. Accountability becomes a necessary principle for the trustworthiness of open computer systems. It regards the responsibility and liability for the data handling performed by a computer system on behalf of an organization. In case of misconduct (e.g. security breaches, personal data leak, etc.), accountability should imply remediation and redress actions, as in the real life.

In 2015, we have contributed two main results: first, techniques for the logic-based definition, analysis and verification of accountability properties; second, a new framework for the compositional definition of privacy-properties and their type-based enforcement.

Logic-based accountability properties

We have proposed a framework for the representation of accountability policies [37] . This framework comes with two novel accountability policy languages; the Abstract Accountability Language (AAL), which is devoted to the representation of preferences/obligations in an human readable fashion, and a concrete one for the mapping to concrete enforceable policies. Our efforts have focused on a formal foundation for the AAL language and some applications.

We have also introduced an approach to assist the design of accountable applications [21] . In particular, we consider an application’s abstract component design and we introduce a logical approach allowing various static verification. This approach offers effective means to early check the design and the behavior of an application and its offered/required services. We motivate our work with a realistic use case coming from the A4Cloud project and validate our proposal with experiments using the TSPASS theorem prover. This prover is competitive with other model-checkers and sat solvers and we gain a more abstract approach than with our previous experiment with a model-checker. It makes also easier the link with end users, for instance privacy officers.

To give a formal foundation of the AAL language we define a translation into first-order temporal logic [20] . We introduce a formula to interpret accountability and a natural criterion to achieve the accountability compliance of two clauses. We continue to apply it to an health care system taking into account data privacy features, data transfers and location processing. We demonstrate few heuristics to speed up the resolution time and to assist in conflict detection. Tool support (AccLab) has been provided to support editing, checking and proving AAL clauses.

Composition of Privacy-Enforcement Techniques

Today's large-scale computations, e.g., in the Cloud, are subject to a multitude of risks concerning the divulging and ownership of private data. Privacy risks are mainly addressed using a large variety of encryption-based techniques. We have proposed a compositional approach for the declarative and correct composition of privacy-preserving applications in the Cloud [22] , [38] . Our approach provides language support for the compositional definition of encryption-based and fragmentation-based privacy-preserving algorithms. This language comes equipped with a set of laws that allows us to verify privacy properties. We have provided implementation support in Scala that ensures certain privacy properties by construction using advanced features of Scala's type system.

Modular systems

Modularity for Javascript Interpreters.

With an initial motivation based on the security of web applications written in JavaScript, we have provided new techniques for the instrumentation of an interpreter for a dynamic analysis as a crosscutting concern [31] . We have defined the instrumentation problem — an extension to the expression problem with a focus on modifying interpreters. We have then shown how we can instrument an interpreter for a simple language using only the bare language features provided by JavaScript.