The proliferation of Vehicular Ad-hoc Networks (VANETs) has brought new security challenges, as malicious vehicles may disseminate fake messages, thereby threatening road safety. Therefore, it is crucial to ensure the credibility of emergency messages while enabling their rapid dissemination. Cloud computing can enhance the efficiency of VANETs, thus facilitating the application of cloud-assisted security mechanisms. Therefore, this paper proposes a Cloud-assisted Multi-dimensional Reputation Management (CMRM) scheme with privacy preservation for emergency message dissemination in VANETs. Specifically, vehicles are represented by multi-dimensional reputation vectors together with dynamically updated multi-dimensional threshold vectors, which enable more fine-grained and reliable reputation evaluation. A confusing process is employed to conceal vehicle identities, reputation vectors, and threshold vectors, thereby ensuring privacy preservation. Furthermore, we design a Reputation Judgment Vector Extraction (RJVE) algorithm. This algorithm, through the collaboration of two cloud servers, can obtain the reputation judgment vector without disclosing sensitive data. Based on this, receivers use the Credible Message Judgment (CMJ) algorithm to efficiently evaluate the credibility of emergency messages. Theoretical analysis demonstrates that the CMRM scheme achieves privacy preservation and resists common attacks with low computation and communication overhead on both the Trusted Authority (TA) and vehicle sides. Simulation results further verify the robustness and efficiency of the CMRM scheme. The probability that a true message is trusted can quickly converge to over 80%, and the probability that a fake message is trusted quickly drops to near 0.

Vehicle platoon, where multiple vehicles travel in formation under a leading vehicle, enhances road capacity and reduces energy consumption. Assessing the reliability of the leading vehicle through reputation management is critical for the vehicle platoon. In the domain of reputation management, reputation updating is of paramount importance. However, many existing schemes are limited by security vulnerabilities, privacy concerns, and reliance on simplistic strategies (i.e., single reputation updating and single-dimensional evaluation), with this reliance undermining their robustness. To address these issues, this paper proposes a Privacy-Preserving Dual Reputation Updating Scheme with Multi-Dimensional Feedback Scores in Vehicle Platoon (PDRU). The PDRU scheme employs a dual reputation model, which enhances the robustness of the reputation updating and provides resilience against the single reputation attack. Meanwhile, it introduces a multi-dimensional evaluation frame work that enables following vehicles to assess the leading vehicle across multiple dimensions, with feedback scores aggregated through weighted averaging according to the importance of each dimension. Moreover, it preserves the vehicle identity privacy, feedback score privacy, leading vehicle's reputation value privacy, and following vehicle's reputation value privacy. Theoretical analysis and simulation evaluation demonstrate that the PDRU scheme achieves a strong balance between robustness, privacy, security, and efficiency, particularly in reducing computation and communication overheads on the Trusted Authority (TA) side.

Nowadays, many researchers design certificateless aggregate signature (CLAS) authentication schemes with pseudonyms for vehicular ad-hoc networks (VANETs) to ensure data integrity, source authentication, and user privacy-preserving. Unfortunately, our analysis reveals that even the state-of-the-art schemes cannot be directly applied to VANETs as they are either not entirely secure or inefficient. Therefore, building on the insights of previous research, we propose a secure and efficient CLAS scheme with pseudonyms for VANETs, which is based on elliptic curve cryptography (ECC) construction and without bilinear pairing (pairing-free). Then, we specifically introduce the generalized forking lemma to enhance the transparency of the security proof process. Based on standard cryptographic assumptions, we prove that the proposed CLAS scheme can withstand attacks from Type-I, Type-II, and Type-III adversaries while satisfying various security and privacy requirements in VANETs. Finally, performance analysis shows that compared to the latest pairing-free CLAS schemes in VANETs, the proposed CLAS scheme not only offers more comprehensive security but also has lower computational and communication overhead. Additionally, we also utilized the MIRACL cryptography library for simulation experiments, and the results indicate that the proposed scheme still performs lower overhead in practical simulation environments, making it more suitable for resource-constrained VANET environments.