Secure message dissemination is an important issue in vehicular networks, especially considering the vulnerability of vehicle to vehicle message dissemination to malicious attacks. Traditional security mechanisms, largely based on message encryption and key management, can only guarantee secure message exchanges between known source and destination pairs. In vehicular networks however, every vehicle may learn its surrounding environment and contributes as a source, while in the meantime act as a destination or a relay of information from other vehicles, message exchanges often occur between "stranger" vehicles. For secure message dissemination in vehicular networks against insider attackers, who may tamper the content of the disseminated messages, ensuring the consistency and integrity of the transmitted messages becomes a major concern that traditional message encryption and key management based approaches fall short to provide. In this paper, by incorporating the underlying network topology information, we propose an optimal decision algorithm that is able to maximize the chance of making a correct decision on the message content, assuming the prior knowledge of the percentage of malicious vehicles in the network. Furthermore, a novel heuristic decision algorithm is proposed that can make decisions without the aforementioned knowledge of the percentage of malicious vehicles. Simulations are conducted to compare the security performance achieved by our proposed decision algorithms with that achieved by existing ones that do not consider or only partially consider the topological information, to verify the effectiveness of the algorithms. Our results show that by incorporating the network topology information, the security performance can be much improved. This work shed light on the optimum algorithm design for secure message dissemination.
Vehicular ad hoc networks (VANETs) have the potential to transform the way people travel through the creation of a safe interoperable wireless communications network that includes cars, buses, traffic signals, cell phones, and other devices. However, VANETs are vulnerable to security threats due to increasing reliance on communication, computing, and control technologies. The unique security and privacy challenges posed by VANETs include integrity (data trust), confidentiality, nonrepudiation, access control, real-time operational constraints demands, availability, and privacy protection. The trustworthiness of VANETs could be improved by addressing holistically both data trust, which is defined as the assessment of whether or not and to what extent the reported traffic data are trustworthy, and node trust, which is defined as how trustworthy the nodes in VANETs are. In this paper, an attack-resistant trust management scheme (ART) is proposed for VANETs that is able to detect and cope with malicious attacks and also evaluate the trustworthiness of both data and mobile nodes in VANETs. Specially, data trust is evaluated based on the data sensed and collected from multiple vehicles; node trust is assessed in two dimensions, i.e., functional trust and recommendation trust, which indicate how likely a node can fulfill its functionality and how trustworthy the recommendations from a node for other nodes will be, respectively. The effectiveness and efficiency of the proposed ART scheme is validated through extensive experiments. The proposed trust management theme is applicable to a wide range of VANET applications to improve traffic safety, mobility, and environmental protection with enhanced trustworthiness. Vehicular ad hoc networks (VANETs) are essentially used to communicate real-time traffic and safety information. In this paper, we present vehicular security through reputation and plausibility checks to address the most important issue of security in VANETs. The algorithm provides security against the attacks of event modification, false event generation, data aggregation and data dropping. It performs not only detection but also the isolation of malicious nodes in the network. It employs sensors in a reputation-based system and presents a very robust yet cost efficient approach as it utilizes just vehicle to vehicle communication, thereby reducing the security issues and cost associated with the roadside infrastructure. The algorithm has been simulated and tested on various scenarios and has been observed to be very effective and efficient in terms of the percentage of malicious nodes detected, number of control packets sent after detection of malicious nodes, average time taken to detect nodes which are generating false information, number of packets dropped, and the number of packets received by malicious nodes.