The Internet of Things (IoT) aims for connecting Anything, Anywhere, Anytime (AAA). This premise brings about heterogeneity that creates connectivity challenges. These challenges constitutes a serious obstacle to interoperability between things. Most existing approaches tackles the interoperability problem by avoiding heterogeneity with standards at runtime. While heterogeneity is an intrinsic feature of the IoT, there is a need for an approach that embraces it to connect AAA. In this paper we propose a model-based methodology to tackle the interoperability problem. It relies on a Domain-Specific Language (DSL) for a model-based specification of the network and a transformation process to generate the network artifacts from this specification. The principle consists of achieving interoperability at the model-level, then during a transformation process, ensuring that it is preserved in the low-level code. Adopting this methodology makes the engineering of the IoT more rigorous, prevents bugs earlier and saves time.

Analyzing and fixing problems of complex rule-based policies, like inconsistencies and conflicts, is a well-known topic in security. In this paper, by leveraging previous work on enumerating all the problematic requests for a rule-based system, we define an operation on the policy that removes these problems. While the final fix remains a typically manual activity, removing conflicts allows the user to work on unambiguous policies, produced automatically. We prove the main properties of the problem removal operation on rule-based systems in first-order logic. We propose an optimized process to automatically perform problem removal by reducing time and size of the policy updates. Finally we apply it to an administrative role-based access control (ARBAC) policy and an attribute-based access control (ABAC) policy, to illustrate its use and performance.

Model-Driven Engineering (MDE) is a paradigm that favors using models to address software engineering problems. Very few attempts have been made to apply this paradigm to the Internet of Things (IoT). Most of the existing MDE approaches focus on abstracting the heterogeneity of IoT things while neglecting network communication heterogeneity. In fact, few attempts target network-based IoT applications. In this paper, we propose a framework, called CyprIoT, to model and control network-based IoT applications using MDE techniques. Our approach relies on 1) Networking Language, to model a network of IoT things 2) Rule-Based Policy Language, to control and supervise the behavior of the modeled network 3) Code Generator, to interpret the model and generate deployable network artifacts and 4) Plug-in System, to customize, enhance or implement expert knowledge into the generated artifacts.

Rule-based systems are used to define complex policies in several contexts, because of the flexibility and modularity they provide. This is especially critical for security systems, which may require to compose evolving policies for privacy, accountability, access control, etc. The inclusion of conflicting rules in complex policies, results in the inability of the system to unambiguously answer to certain requests, with possibly unpredictable effects. The static identification of these undefined requests is particularly challenging for unconstrained rule-based systems, including quantifiers, computations and chaining of rules. In this paper we introduce a static method to precisely characterize the set of all undefined requests for a given unconstrained rule-based system, providing the user with a global view of the rule conflicts. We propose an enumerative approach, made usable in practice by two key performance optimizations: a finer classification of the rules and the resort of the topological sorting. We demonstrate its application on a well-known policy with more than fifty rules.

Accountability is the driving principle for several of regulatory frameworks such as the European Union's General Data Protection Regulation (EU GDPR), the Health Insurance Portability and Accountability Act (HIPAA) and the Corporate and Auditing Accountability and Responsibility Act, thus influencing how organizations run their business processes. It is a central concept for enabling trust and assurance in cloud computing and future internet-based services that may emerge. Nevertheless, accountability can have different interpretations according to the level abstraction. This leads to uncertainty concerning handling and responsibility for data in computer systems with outsourcing supply-chains, as in cloud computing. When defining policies to govern organizations, we need tools to model accountability in rich contexts, including concepts like multiple agents, obligations, remediation actions and temporal aspects. The Abstract Accountability Language (AAL) is built on logical foundations allowing to describe real-world scenarios involving accountability concerns. Its semantic principles provide us means to answer whether the conditions to reach accountability in a given context are met. Moreover, we created a tool support to verify and monitor accountability policies.

Most of existing Model-Driven Engineering (MDE) approaches for the Internet of Things (IoT) focus on means of modeling the behavior of end devices. Little attention has been paid to network-related abstractions and communication control. The paper introduces an approach towards enabling model-based communication control in a network of things. First, we suggest a Domain Specific Language (DSL) to abstract basic network features. Second, we propose a policy language to control the communications within the network. Finally, as a proof-of-concept, we present a code generation process to enforce the expressed policy at runtime.

Accountability means to obey a contract and to ensure responsibilities in case of violations. In previous work we defined the Abstract Accountability Language (AAL) and its AccLab tool support. In order to evaluate the suitability of our language and tool we experiment with the laptop user agreement, one of the policies of the Hope University in Liverpool.

The goal of AccMon is to provide means to monitor accountability policies in the context of a real system. The tool allows to specify policies that are applicable to network traffic, web application code and external components via plugins. These policies are based on a distributed temporal logic with data. The framework allows centralized or distributed monitoring and both on-line and off-line controls. AccMon is interconnected with another tool called AccLab (Accountability Laboratory) which allows to define abstract accountability policies and check their satisfiability and compliance.

Security and privacy requirements in ubiquitous systems need a sophisticated policy language with features to express access restrictions and obligations. Ubiquitous systems involve multiple actors owning sensitive data concerning aspects such as location, discrete and continuous time, multiple roles that can be shared among actors or evolve over time. Policy consistency is an important problem in languages supporting these aspects. In this paper we present an abstract language (AAL) to specify most of these security and privacy features and compare it with XACML. We also classified the existing conflict detection mechanisms for XACML in dynamic, testing, or static detection. A thorough analysis of these mechanisms reveals that they have several weaknesses and they are not applicable in our context. We advocate for a classic approach using the notion of logical consistency to detect conflicts in AAL.

The French IRT-Nanoelec consortium in collaboration with GENEPI2 accelerator is offering world unique and complementary techniques for Hirel components characterisation. Part of this capability is the high and low (thermal) energy neutron testing of devices.

The widespread adoption of the cloud model for service delivery triggered several data protection issues. As a matter of fact, the proper delivery of these services typically involves sharing of personal/business data between the different parties involved in the service provisioning. In order to increase cloud consumer's trust, there must be guarantees on the fair use of their data. Accountability provides the necessary assurance about the data governance practices to the different stakeholders involved in a cloud service chain. In this context, we propose a framework for the representation of accountability policies. Such policies offer to end-users a clear view of the privacy and accountability clauses asserted by the entities they interact with, as well as means to represent their preferences. Our framework offers two accountability policy languages: (i) an abstract language called AAL devoted for the representation of preferences/clauses in an human readable fashion, and (ii) a concrete one for the implementation of enforceable policies.

Today on-line services are the cornerstone of on-line applications such as e-commerce, e-government and e-health applications. However, they raise several challenges about data privacy. Accountability, which is the property of an entity of being responsible for its acts, meets some of these challenges and hence increases user's trustworthiness in on-line applications. In this work, we propose an approach to assist the design of accountable applications. In particular, we consider an application's abstract component design and we introduce a logical approach allowing various static verifications. 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 a theorem prover.

With the rise of the services-based economy and the democratization of on-line services, more and more users (individual and/or business) use on-line applications in their daily lives. Usually personal data transits between different actors involved in a service's delivery chain (e.g. application/storage service providers) and thus might raise some privacy issues. Accountability, which is the property of an entity of being responsible for its acts, can help mitigate data privacy and data disclosures issues in such applications. In this paper, we propose a translational semantics for our accountability language and we present some expected properties. We introduce a natural criterion to achieve the accountability compliance of two clauses and few heuristics to speed up the resolution time. We demonstrate the feasibility of our verification process with a realistic health care use case and the TSPASS theorem prover.

Grenoble, France, is home to one of the four large R&D and production sites in Europe for microelectronics chips. What sets it apart is that Grenoble is also one of the best sites in the world for academic research when it comes to analyzing and characterizing atomic structures and materials using synchrotron X-rays and neutrons. The European Synchrotron Radiation Facility (ESRF) and the Institut Laue-Langevin (ILL) are co-hosted next to the French technology research organization's CEA-LETI center and the ST Microelectronics R&D laboratories. However, it is not only for this reason that the challenge of harnessing the power of the ESRF and the ILL for industrial R&D been taken up by the ESRF and the ILL ever since they opened for business [1 S. Malbet-Monaco, Acta Cryst. D 69, 1289 (2013).[Crossref], [PubMed], [Web of Science ®] , [Google Scholar], 2 E. Mitchell, SRN 24(6), 18 (2012). [Google Scholar]].

Nowadays we are witnessing the democratization 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 flowed 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. In fact, dealing with personal data raises several privacy and accountability issues that must be considered before to promote the use of cloud services. In this paper, we propose a framework for the representation of cloud accountability policies. Such policies offer to end-users a clear view of the privacy and accountability obligations asserted by the entities they interact with, as well as means to represent their preferences. This framework comes with two novel accountability policy languages. An abstract one devoted for the representation of preferences/obligations in an human readable fashion. And a concrete one for the mapping to concrete enforceable policies. We motivate our solution with concrete use case scenarios.

The goal of the PASCS track is to offer academic and industrial researchers and practitioners a platform for discussions related to privacy and accountability issues in software components and cloud services. For this first edition of PASCS we received 8 submissions. The program committe selected 3 long papers for presentation and publication in the WETICE proceedings on the basis of the originality, quality, and relevance to the topics of the track. Each submission received is reviewed at least by three reviewers.