MARINE: Man-in-the-middle attack resistant trust model IN connEcted vehicles

Vehicular Ad-hoc NETwork (VANET), a novel technology holds a paramount importance within the transportation domain due to its abilities to increase traffic efficiency and safety. Connected vehicles propagate sensitive information which must be shared with the neighbors in a secure environment. However, VANET may also include dishonest nodes such as Man-in-the-Middle (MiTM) attackers aiming to distribute and share malicious content with the vehicles, thus polluting the network with compromised information. In this regard, establishing trust among connected vehicles can increase security as every participating vehicle will generate and propagate authentic, accurate and trusted content within the network. In this paper, we propose a novel trust model, namely, Man-in-the-middle Attack Resistance trust model IN connEcted vehicles (MARINE), which identifies dishonest nodes performing MiTM attacks in an efficient way as well as revokes their credentials. Every node running MARINE system first establishes trust for the sender by performing multi-dimensional plausibility checks. Once the receiver verifies the trustworthiness of the sender, the received data is then evaluated both directly and indirectly. Extensive simulations are carried out to evaluate the performance and accuracy of MARINE rigorously across three MiTM attacker models and the bench-marked trust model. Simulation results show that for a network containing 35% MiTM attackers, MARINE outperforms the state of the art trust model by 15%, 18%, and 17% improvements in precision, recall and F-score, respectively.N/A

Emerging privacy challenges and approaches in CAV systems

The growth of Internet-connected devices, Internet-enabled services and Internet of Things systems continues at a rapid pace, and their application to transport systems is heralded as game-changing. Numerous developing CAV (Connected and Autonomous Vehicle) functions, such as traffic planning, optimisation, management, safety-critical and cooperative autonomous driving applications, rely on data from various sources. The efficacy of these functions is highly dependent on the dimensionality, amount and accuracy of the data being shared. It holds, in general, that the greater the amount of data available, the greater the efficacy of the function. However, much of this data is privacy-sensitive, including personal, commercial and research data. Location data and its correlation with identity and temporal data can help infer other personal information, such as home/work locations, age, job, behavioural features, habits, social relationships. This work categorises the emerging privacy challenges and solutions for CAV systems and identifies the knowledge gap for future research, which will minimise and mitigate privacy concerns without hampering the efficacy of the functions

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