Existing conditional privacy-preserving communication protocols based on a tamper-proof device (TPD) in vehicular ad hoc networks (VANETs) face the challenges of master key compromise and vehicle revocation. To address these challenges, we propose a new identity-based anonymous authentication scheme. In this scheme, the master key of the system will not be directly installed in the TPD; hence, it is impossible for an adversary to obtain the system master key from the TPD. To generate the private key of the vehicle, an additional secret is required, and this secret is provided by the roadside unit (RSU). Therefore, revoking a malicious vehicle from the VANETs is efficient, since the RSU only needs to stop generating the up-to-date secret for the vehicle. In addition, the signature verification algorithm of the scheme involves no bilinear pairing operations, making the verification process more efficient. The security of the scheme is proved to be equivalent to the elliptic curve discrete logarithm assumption in the random oracle. The experimental results show that the authentication of the scheme is more efficient, and the communication cost has been diminished.

Cloud computing enables users to remove the necessity of the need of local hardware architecture, which removes the burden of the users from high computation costs. Therefore, it has attracted much attention and research has been conducted heavily on it. To protect users' privacy, data is usually encrypted prior to being sent to the cloud server. New cryptographic primitive such as public-key encryption with equality test (PKEET) has been introduced to make it more practical. In PKEET, users can test whether the underlying messages of two ciphertexts encrypted under different public keys are equal or not without the need to decrypt those ciphertexts. This is a very useful tool, especially for the cloud database, since PKEET mainly focuses on the equality test between two ciphertexts. However, in practice, the cloud server may need to verify the equivalence among more than two ciphertexts. This leads to disclosing unnecessary information of users and redundant computation cost will also occur when using traditional PKEET schemes. How to make this more efficient and practical remains an interesting research problem. In this paper, to solve the aforementioned problems by providing a novel concept of public-key encryption with multi-ciphertext equality test (PKE-MET).

Patient-centered data management and sharing of personal health records (PHRs) are difficult to be realized as data is controlled by doctors/hospitals. In addition, security and privacy, oppressive costs, search and tracing unreliability, and complicated access authorization caused by traditional encryption severely hinder the widespread adoption of PHRs. To overcome these challenges, we propose a blockchain-backed data sharing framework for PHRs, where the blockchain achieves reliable search and tracing. Furthermore, we design a hybrid b lock c hain-backed s earchable p roxy s ign c ryption scheme, named BC-SPSC . Specifically, an identity-based proxy signature (IBPS) is utilized to perform the authorization from patients to doctors to achieve authentic patient-centricity, therefore the blockchain can relate data with associated patients and doctors during data tracing. Moreover, BC-SPSC supports two search modes. The first mode adopts attribute-based encryption with keyword-based search (SABE), where all legitimate users can implement searches, but only users whose attributes satisfy the access structure can successfully decrypt. By contrast, the second mode utilizes attribute-based searchable encryption (ABSE) to accomplish fine-grained authorization in both search and data access/decryption, that is, who can search is also constrained by data owners. Adequate performance comparisons and simulation experiments indicate significant advantages of the BC-SPSC scheme in storage and computation overheads.

To know the most recent market conditions, an e-commerce platform needs to be aware of the sales situation of its sellers’ commodities. The most recent market conditions can help to forecast future market trends and develop policies to guide sellers in reasonably allocating their inventory proportion. Statistical analysis is a fundamental approach to studying the sales situation. However, the sales data of an e-commerce platform usually has a significant volume. Therefore, outsourcing statistical analysis to cloud servers is an effective method. Nevertheless, sellers do not want their sales data leaked to anyone or any other organization. Moreover, in many circumstances, we cannot fully trust cloud servers. Thus, we need to utilize cryptographic or non-cryptographic tools to realize the above outsourcing. Secret sharing is a lightweight and powerful non-cryptographic tool to realize privacy-preserving data analysis. However, it needs secure channels to distribute secret shares. On the other hand, homomorphic encryption is a powerful cryptographic tool for designing privacy-preserving data analysis schemes. Nevertheless, these schemes usually do not allow the entity that holds the decryption key to collude with other entities. We propose a privacy-preserving and verifiable statistical analysis scheme for an e-commerce platform that combines a threshold secret sharing scheme with a verifiable threshold homomorphic encryption scheme. Our solution’s demand for secure channels is reduced by 40% ~ 60% compared with a traditional threshold secret sharing scheme, thanking the designed novel distribution model for delivering secret shares. Furthermore, our solution has a stronger ability to resist collusive attacks, keep sales data private from any entity, and ensure that the platform can only obtain the analysis results with the help of some cloud servers, alleviating the single point of trust. And meanwhile, the novel distributed model makes our solution enjoy better robustness and fault tolerance. The proposed solution is validated through security analyses, performance evaluations, and comparison analyses.