Smart vehicle applications play a crucial role in intelligent transportation systems, enabling sensor-equipped vehicles to establish dynamic networks for efficient collection, sharing, and aggregation. This significantly enhances road security and efficiency by transmitting crucial information to traffic authorities. However, partial research on certificateless aggregation signcryption (CLAS) scheme reveals an intriguing phenomenon where each proposed scheme consistently exhibits numerous security vulnerabilities, particularly susceptible to public key replacement attacks. To address these challenges, this paper proposes a blockchain-assisted certificateless aggregation sign-cryption scheme (BACLAS), leveraging blockchain technology to securely store users’ public key on a distributed ledger and prevent public key replacement attacks effectively. Furthermore, it is a provably secure communication scheme for real-world Vehicle-to-Infrastructure (V2I) communication while addressing practical security concerns. The BACLAS scheme ensures security in terms of existential unforgeability against adaptive chosen message attacks (EUF-CMA) and indistinguishability against adaptive chosen ciphertext attacks (IND-CCA2) based on the hardness assumption of the elliptic curve discrete logarithm problem and computational Diffie-Hellman problem in the random oracle model. The proposed scheme effectively reduces computational costs and time consumption, resulting in a significant reduction of the computation burden ranging from 50.02% to 88.28% compared to other competitive schemes. Moreover, it successfully addresses the key-escrow problem, thereby achieving enhanced security properties.

The advancement of spatial positioning technology and mobile Internet makes it possible for location-based services (LBSs), which provide users with personalized services by collecting and analyzing their location information. The$k$-nearest neighbor (kNN) query algorithm can be used in LBS by returning$k$locations closest to the target location. Due to the fact that LBS involves large amounts of private information and is usually outsourced to cloud servers, privacy issues have become increasingly prominent. In order to provide LBS services in outsourced cloud environments while protecting user location privacy, a privacy-aware kNN protocol under the dual cloud server model is presented. In the proposed scheme, location-related information is encrypted using a double-trapdoor public-key encryption algorithm and stored in a$k$-dimension (KD)-tree before being outsourced to cloud servers. A Euclidean distance protocol and a comparison protocol are provided as basic components to realize secure search, insertion, and deletion of the encrypted KD-tree by the cooperation of two cloud servers. Security analysis indicates that the proposed scheme ensures location and query privacy. Performance evaluation results demonstrate that the scheme is practical in terms of time and communication consumption.

With the rapid advancement of wireless communication and autonomous driving technology, vehicular ad hoc networks (VANETs) has emerged as a robust network facilitating interactive communication among vehicles, roadside infrastructure, and the surrounding environment. However, VANETs face challenges regarding traffic information security and vehicle identity privacy during wireless transmission. Vehicles require reliable technology to communicate efficiently and securely with roadside infrastructure, especially at high speeds. To address these issues in VANETs environments characterized by diverse nature of vehicles and roadside units (RSUs), we propose an enhanced certificateless and identity-based offline/online heterogeneous signcryption (CLIOOHSC) scheme for VANETs, aiming to achieve confidentiality, integrity, authentication and identity anonymity simultaneously in a unified step. The CLIOOHSC scheme enables vehicles in certificateless cryptography (CLC) environment to transmit messages to RSU in identity-based cryptography (IBC) environment. In the online phase, scalar multiplication operations are omitted since they are performed in the offline phase, significantly reducing the computational load. Then, through security proofs, we demonstrate that the proposed scheme can achieve the expected security properties. The performance analysis shows that our scheme is superior to other schemes in terms of computation and communication costs and is suitable for scenarios where vehicles communicate across cryptosystems.

Ensuring the security and privacy of users and data in a mobile-edge computing (MEC) deployment, without affecting performance, latency and user quality of experience remain challenging. For example, in this article, we revisit an identity-based anonymous authentication scheme designed for MEC deployment. Then, we reveal that the scheme is vulnerable to impersonation, replay, and Denial-of-Service (DoS) attacks, contrary to their claims. It also does not achieve user untraceability, and the registration center must be online during authentication. We also observe that it is unclear from their scheme description, what encryption algorithm should be used in the authentication process. Therefore, we redesign the scheme in order to mitigate the weaknesses pointed out. Our redesigned protocol uses password and biometrics for authentication, which broadens the scope for real-world implementation. We also provide both formal security proof and heuristic security analysis to demonstrate that the proposed scheme achieves the desired security goals. A performance comparison shows that our scheme outperforms four other competing schemes in terms of computation and communication costs.

Benefiting from the progress of Internet of Things (IoT) technology, medical devices, wearables, sensors, and users can be connected with each other to form an Internet of Medical Things (IoMT) ecosystem. IoMT improves efficiency, increases accuracy, and reduces the costs of the traditional healthcare system. However, since IoMT involves different entities and heterogeneous networks and carries a large amount of private information, it is a challenging task to ensure data security and protect privacy in the IoMT ecosystem. In this article, we focus on the issue of privacy-aware authentication between entities. We first propose a blockchain-assisted authentication framework for IoMT applications in the fog computing paradigm. Furthermore, we present two privacy-preserving authentication protocols based on elliptic curve cryptography (ECC) and physically unclonable functions (PUFs), respectively, in terms of the capacity of involved entities. Security analysis and performance evaluation demonstrate that compared with several previous protocols, the proposed protocols have competitive computation and communication costs while achieving expected security requirements.