Biblio

The transportation sector is undergoing rapid changes to reduce pollution and increase life quality in urban areas. One of the most effective approaches is flexible car rental and sharing to reduce traffic congestion and parking space issues. In this paper, we envision a flexible car sharing framework where vehicle owners want to make their vehicles available for flexible rental to other users. The owners delegate the management of their vehicles to intermediate services under certain policies, such as municipalities or authorized services, which manage the due infrastructure and services that can be accessed by users. We investigate the design of an accountable solution that allow vehicles owners, who want to share their vehicles securely under certain usage policies, to control that delegated services and users comply with the policies. While monitoring users behavior, our approach also takes care of users privacy, preventing tracking or profiling procedures by other parties. Existing approaches put high trust assumptions on users and third parties, do not consider users' privacy requirements, or have limitations in terms of flexibility or applicability. We propose an accountable protocol that extends standard delegated authorizations and integrate it with Security Credential Management Systems (SCMS), while considering the requirements and constraints of vehicular networks. We show that the proposed approach represents a practical approach to guarantee accountability in realistic scenarios with acceptable overhead.

Designing secure, scalable, and resilient IoT networks is a challenging task because of resource-constrained devices and no guarantees of reliable network connectivity. Fog computing improves the resiliency of IoT, but its security model assumes that fog nodes are fully trusted. We relax this latter constraint by proposing a solution that guarantees confidentiality of messages exchanged through semi-honest fog nodes thanks to a lightweight proxy re-encryption scheme. We demonstrate the feasibility of the solution by applying it to IoT networks of low-power devices through experiments on microcontrollers and ARM-based architectures.