With the rapid growth of cloud storage user scale, there are dual challenges of resource waste and security hazards in massive data storage: on the one hand, redundant data exacerbates storage overhead; on the other hand, unauthorized access exacerbates the possibility of data leakage or tampering. To this end, this paper designs a shared data auditing scheme that supports fine-grained access control and cloud deduplication. First, combining Random Convergent Encryption (RCE), Proof-of-Ownership (PoW) technology, and introducing a certificate-less cryptosystem to securely deduplicate data in the cloud while eliminating certificate management and key escrow risks. Second, the data is encrypted using Ciphertext-Policy Attribute-Based Encryption (CP-ABE) technology, and only authorized users can decrypt the data based on attribute matching, which can effectively resist the risk of data leakage due to unauthorized access. At the same time, we designate an auditor to carry out data integrity auditing to prevent malicious audit behavior. Finally, Security and performance evaluations show that the scheme we’ve proposed is quite efficient and competitive.

With the arrival of the era of self-driving technology, 5G, and IoT technology, self-driving car Internet technology is gradually changing the way people travel. The existing signcryption scheme test scheme with equality can only compare two ciphertexts, which is not suitable for the complex network of Internet of vehicles. To address this challenge, we propose the heterogeneous signcryption scheme from public key infrastructure (PKI) to identity-based cryptosystem (IBC) with multi-ciphertext equality test in the Internet of vehicles (HSCPI-MET). This scheme enables to communicate from PKI cryptosystem to IBC cryptosystem in Internet of vehicles, at the same time excuting the equality test of multi-ciphertext. Our scheme protects inter-vehicle communication data from being illegally accessed, tampered, or forged by malicious vehicles. The proposed scheme satisfies confidentiality and unforgeability under the stochastic predictor model for the computational Diffie–Hellman assumption and the IDH assumption. In addition, we conduct a rigorous experimental evaluation of the scheme to prove that it is secure and effective in practical applications.

Vehicular ad-hoc networks (VANETs) are integral to the evolution of intelligent transportation systems, offering substantial benefits in managing traffic flow, issuing warnings for potential accidents, and delivering information services to drivers. To ensure the authenticity and integrity of data exchanged within VANETs, numerous authentication schemes based on certificateless aggregate signature (CLAS) have been developed. However, state-of-the-art solutions often fail to be applicable in real-world VANETs due to security weaknesses and operational inefficiencies. Recently, Zhu et al. proposed an efficient CLAS-based authentication scheme with conditional privacy preservation (CPP) for VANETs (IEEE Transactions on Intelligent Transportation Systems, DOI: 10.1109/TITS.2023.3275077). Unfortunately, our analysis reveals that Zhu et al.’s scheme is incapable of withstanding coalition attacks from malicious RSUs and vehicles as well as public-key replacement attacks from dishonest vehicles. To facilitate secure communication in VANETs, we present a security-enhanced, pairing-free and energy-efficient CLAS-based authentication scheme with CPP for VANETs. This scheme has been rigorously proven to be secure against Type I, Type II and Type III attackers. Distinguished from other comparable schemes, our construction significantly reduces communication overhead and energy consumption while simultaneously fortifying security.