An Anonymous Certificateless Signcryption Scheme for Secure and Efficient Deployment of Internet of Vehicles

Abstract

Internet of Vehicles (IoV) is a specialized breed of Vehicular Ad-hoc Networks (VANETs) in which each entity of the system can be connected to the internet. In the provision of potentially vital services, IoV transmits a large amount of confidential data through networks, posing various security and privacy concerns. Moreover, the possibility of cyber-attacks is comparatively higher when data transmission takes place more frequently through various nodes of IoV systems. It is a serious concern for vehicle users, which can sometimes lead to life-threatening situations. The primary security issue in the provision of secure communication services for vehicles is to ensure the credibility of the transmitted message on an open wireless channel. Then, receiver anonymity is another important issue, i.e., only the sender knows the identities of the receivers. To guarantee these security requirements, in this research work, we propose an anonymous certificateless signcryption scheme for IoV on the basis of the Hyperelliptic Curve (HEC). The proposed scheme guarantees formal security analysis under the Random Oracle Model (ROM) for confidentiality, unforgeability, and receiver anonymity. The findings show that the proposed scheme promises better security and reduces the costs of computation and communication.

A Resource-Friendly Certificateless Proxy Signcryption Scheme for Drones in Networks beyond 5G

“…In Table 4, we compare the primary operations of communication cost for the proposed scheme and other schemes that were proposed, including those proposed by Yanfeng et al [25], Bhatia and Verma [26], Li et al [27], and Qu and Zeng [28]. As shown in Table 4, NP m represents the message size, which we assume was 2048 bits, NP q represents the parameter size, which belongs to elliptic curve and was equal to 160 bits [30,31], NP ID represents the identity size, which belongs to elliptic curve and was equal to 160 bits, and NP G represents the parameter size, which is part of the bilinear group, and its value was 1024 bits. As detailed in Table 4 and depicted in Figure 3, the proposed scheme had lower communication costs than its counterparts.…”

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A Q-Learning-Based Approximate Solving Algorithm for Vehicular Route Game

“…To reduce the calculations without weakening the contribution description, the pure strategy is adopted in this paper's route game, and it is assumed that the vehicles have the same origin-destination from point O to point D. All vehicles are equipped with IoVs devices and no overtaking occurs. Based on the IoVs technique, the driving data can be exchanged between vehicles in fast-moving [35]. Each vehicle has to choose a path to its destination D. Let E = {ε|ε = 1, 2, .…”