A trust-driven privacy architecture for vehicular ad-hoc networks

Vehicular Ad-Hoc NETworks (VANETs) are an emerging technology which aims to improve road safety by preventing and reducing traffic accidents. While VANETs offer a great variety of promising applications, such as, safety-related and infotainment applications, they remain a number of security and privacy related research challenges that must be addressed. A common approach to security issues widely adopted in VANETs is the use of Public Key Infrastructures (PKI) and digital certificates in order to enable authentication, authorization and confidentiality. These approaches usually rely on a large set of regional Certification Authorities (CAs). Despite the advantages of PKI-based approaches, there are two main problems that arise, i) the secure interoperability among the different and usually unknown- issuing CAs, and ii) the sole use of PKI in a VANET environment cannot prevent privacy related attacks, such as, linking a vehicle with an identifier, tracking vehicles ¿big brother scenario" and user profiling. Additionally, since vehicles in VANETs will be able to store great amounts of information including private information, unauthorized access to such information should be carefully considered. This thesis addresses authentication and interoperability issues in vehicular communications, considering an inter-regional scenario where mutual authentication between nodes is needed. To provide interoperability between vehicles and services among different domains, an Inter-domain Authentication System (AS) is proposed. The AS supplies vehicles with a trusted set of authentication credentials by implementing a near real-time certificate status service. The proposed AS also implements a mechanism to quantitatively evaluate the trust level of a CA, in order to decide on-the-y if an interoperability relationship can be created. This research work also contributes with a Privacy Enhancing Model (PEM) to deal with important privacy issues in VANETs. The PEM consists of two PKI-based privacy protocols: i) the Attribute-Based Privacy (ABP) protocol, and ii) the Anonymous Information Retrieval (AIR) protocol. The ABP introduces Attribute-Based Credentials (ABC) to provide conditional anonymity and minimal information disclosure, which overcome with the privacy issues related to linkability (linking a vehicle with an identifier) and vehicle tracking (big brother scenario). The AIR protocol addresses user profiling when querying Service Providers (SPs), by relying in a user collaboration privacy protocol based on query forgery and permutation; and assuming that neither participant nodes nor SPs could be completely trusted. Finally, the Trust Validation Model (TVM) is proposed. The TVM supports decision making by evaluating entities trust based on context information, in order to provide i) access control to driver and vehicle's private information, and ii) public information trust validation

Secure geolocalization of wireless sensor nodes in the presence of misbehaving anchor nodes

Geolocalization of nodes in a wireless sensor network is a process that allows location-unaware nodes to discover their spatial coordinates. This process requires the cooperation of all the nodes in the system. Ensuring the correctness of the process, especially in the presence of misbehaving nodes, is crucial for ensuring the integrity of the system. We analyze the problem of location-unaware nodes determining their location in the presence of misbehaving neighboring nodes that provide false data during the execution of the process. We divide and present potential misbehaving nodes in four different adversary models, based on their capacities. We provide algorithms that enable the location-unaware nodes to determine their coordinates in the presence of these adversaries. The algorithms always work for a given number of neighbors provided that the number of misbehaving nodes is below a certain threshold, which is determined for each adversary model