A Trust Evaluation Framework in Vehicular Ad-Hoc Networks

Vehicular Ad-Hoc Networks (VANET) is a novel cutting-edge technology which provides connectivity to millions of vehicles around the world. It is the future of Intelligent Transportation System (ITS) and plays a significant role in the success of emerging smart cities and Internet of Things (IoT). VANET provides a unique platform for vehicles to intelligently exchange critical information, such as collision avoidance or steep-curve warnings. It is, therefore, paramount that this information remains reliable and authentic, i.e., originated from a legitimate and trusted vehicle. Due to sensitive nature of the messages in VANET, a secure, attack-free and trusted network is imperative for the propagation of reliable, accurate and authentic information. In case of VANET, ensuring such network is extremely difficult due to its large-scale and open nature, making it susceptible to diverse range of attacks including man-in-the-middle (MITM), replay, jamming and eavesdropping.

Trust establishment among vehicles can increase network security by identifying dishonest vehicles and revoking messages with malicious content. For this purpose, several trust models (TMs) have been proposed but, currently, there is no effective way to compare how they would behave in practice under adversary conditions. Further, the proposed TMs are mostly context-dependent. Due to randomly distributed and highly mobile vehicles, context changes very frequently in VANET. Ideally the TMs should perform in every context of VANET. Therefore, it is important to have a common framework for the validation and evaluation of TMs.

In this thesis, we proposed a novel Trust Evaluation And Management (TEAM) framework, which serves as a unique paradigm for the design, management and evaluation of TMs in various contexts and in presence of malicious vehicles. Our framework incorporates an asset-based threat model and ISO-based risk assessment for the identification of attacks against critical risks. TEAM has been built using VEINS, an open source simulation environment which incorporates SUMO traffic simulator and OMNET++ discrete event simulator. The framework created has been tested with the implementation of three types of TM (data-oriented, entity-oriented and hybrid) under four different contexts of VANET based on the mobility of both honest and malicious vehicles. Results indicate that TEAM is effective to simulate a wide range of TMs, where the efficiency is evaluated against different Quality of Service (QoS) and security-related criteria. Such framework may be instrumental for planning smart cities and for car manufacturers.

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