AN EFFICIENT CROSS-DOMAIN AUTHENTICATION SCHEME FOR INTERNET OF VEHICLES (IOV) BASED ON REPUTATION

With the rapid development of intelligent transportation technologies, the Internet of Vehicles (IoV) has become an essential component of modern transportation systems. However, as the scale of IoV continues to expand, achieving efficient and trustworthy cross-domain authentication has emerged as a critical technical challenge. To address this issue, this paper proposes a blockchain-based reputation framework for IoV, focusing on cross-domain authentication. Specifically, we propose an efficient cross-domain authentication scheme based on short signatures to address the efficiency and security issues in cross-domain authentication. Traditional cross-domain authentication schemes often incur high computational overhead and network bandwidth consumption, especially when there are significant differences in reputation values across different regions, making identity authentication inefficient. To this end, we design a cross-domain authentication algorithm based on reputation value coupling, which dynamically adjusts the reputation values of vehicle nodes according to the reputation weights of different regions. By integrating smart contract technology, the transparency and traceability of the authentication process are ensured. The dual-authentication mechanism based on reputation values further enhances the security and trustworthiness of nodes. Experimental results demonstrate that the proposed authentication scheme not only significantly improves authentication efficiency but also enhances the security and reliability of the IoV system.

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Publication Details

Journal
Journal of Computer Science and Electrical Engineering
Published
2025-03-06
DOI
https://doi.org/10.61784/jcsee3040
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
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article

AN EFFICIENT CROSS-DOMAIN AUTHENTICATION SCHEME FOR INTERNET OF VEHICLES (IOV) BASED ON REPUTATION

Journal of Computer Science and Electrical Engineering
Network Security and Intrusion Detection
article

AN EFFICIENT CROSS-DOMAIN AUTHENTICATION SCHEME FOR INTERNET OF VEHICLES (IOV) BASED ON REPUTATION

article en

Abstract

With the rapid development of intelligent transportation technologies, the Internet of Vehicles (IoV) has become an essential component of modern transportation systems. However, as the scale of IoV continues to expand, achieving efficient and trustworthy cross-domain authentication has emerged as a critical technical challenge. To address this issue, this paper proposes a blockchain-based reputation framework for IoV, focusing on cross-domain authentication. Specifically, we propose an efficient cross-domain authentication scheme based on short signatures to address the efficiency and security issues in cross-domain authentication. Traditional cross-domain authentication schemes often incur high computational overhead and network bandwidth consumption, especially when there are significant differences in reputation values across different regions, making identity authentication inefficient. To this end, we design a cross-domain authentication algorithm based on reputation value coupling, which dynamically adjusts the reputation values of vehicle nodes according to the reputation weights of different regions. By integrating smart contract technology, the transparency and traceability of the authentication process are ensured. The dual-authentication mechanism based on reputation values further enhances the security and trustworthiness of nodes. Experimental results demonstrate that the proposed authentication scheme not only significantly improves authentication efficiency but also enhances the security and reliability of the IoV system.

Journal of Computer Science and Electrical EngineeringVol. 7(1)
Guangzhou Institute of Advanced Technology (CN)
Openalex Percentile: Top 96%
Network Security and Intrusion Detection
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AN EFFICIENT CROSS-DOMAIN AUTHENTICATION SCHEME FOR INTERNET OF VEHICLES (IOV) BASED ON REPUTATION · Journal of Computer Science and Electrical Engineering (2025) | TGRS Research Map | TGRS