VASERP: An Adaptive, Lightweight, Secure, and Efficient RFID-Based Authentication Scheme for IoV

被引:6
作者
Gong, Yinyan [1 ,2 ]
Li, Kuanching [1 ,2 ]
Xiao, Lijun [3 ]
Cai, Jiahong [1 ,2 ]
Xiao, Jiahong [1 ,2 ]
Liang, Wei [1 ,2 ]
Khan, Muhammad Khurram [4 ]
机构
[1] Hunan Univ Sci & Technol, Sch Comp Sci & Engn, Xiangtan 411201, Peoples R China
[2] Hunan Key Lab Serv Comp & Novel Software Technol, Xiangtan 411201, Peoples R China
[3] Shanghai Maritime Univ, Coll Informat Engn, Shanghai 201306, Peoples R China
[4] King Saud Univ, Ctr Excellence Informat Assurance, Riyadh 11653, Saudi Arabia
基金
中国国家自然科学基金;
关键词
authentication; ECC; RFID; Scyther; IoV; PROTOCOL; INTERNET; LOCALIZATION; VEHICLES; CLOUD;
D O I
10.3390/s23115198
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
With the rapid growth in wireless communication and IoT technologies, Radio Frequency Identification (RFID) is applied to the Internet of Vehicles (IoV) to ensure the security of private data and the accuracy of identification and tracking. However, in traffic congestion scenarios, frequent mutual authentication increases the overall computing and communication overhead of the network. For this reason, in this work, we propose a lightweight RFID security fast authentication protocol for traffic congestion scenarios, designing an ownership transfer protocol to transfer access rights to vehicle tags in non-congestion scenarios. The edge server is used for authentication, and the elliptic curve cryptography (ECC) algorithm and the hash function are combined to ensure the security of vehicles' private data. The Scyther tool is used for the formal analysis of the proposed scheme, and this analysis shows that the proposed scheme can resist typical attacks in mobile communication of the IoV. Experimental results show that, compared to other RFID authentication protocols, the calculation and communication overheads of the tags proposed in this work are reduced by 66.35% in congested scenarios and 66.67% in non-congested scenarios, while the lowest are reduced by 32.71% and 50%, respectively. The results of this study demonstrate a significant reduction in the computational and communication overhead of tags while ensuring security.
引用
收藏
页数:19
相关论文
共 43 条
[1]   SecLAP: Secure and lightweight RFID authentication protocol for Medical IoT [J].
Aghili, Seyed Farhad ;
Mala, Hamid ;
Kaliyar, Pallavi ;
Conti, Mauro .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2019, 101 :621-634
[2]   An energy-efficient and secure identity based RFID authentication scheme for vehicular cloud computing [J].
Akram, Waseem ;
Mahmood, Khalid ;
Li, Xiong ;
Sadiq, Mazhar ;
Lv, Zhihan ;
Chaudhry, Shehzad Ashraf .
COMPUTER NETWORKS, 2022, 217
[3]   A robust and anonymous patient monitoring system using wireless medical sensor networks [J].
Amin, Ruhul ;
Islam, S. K. Hafizul ;
Biswas, G. P. ;
Khan, Muhammad Khurram ;
Kumar, Neeraj .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 80 :483-495
[4]   RFID Reader Anticollision Based on Distributed Parallel Particle Swarm Optimization [J].
Cao, Bin ;
Gu, Yu ;
Lv, Zhihan ;
Yang, Shan ;
Zhao, Jianwei ;
Li, Yujie .
IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (05) :3099-3107
[5]   A secured and lightweight RFID-tag based authentication protocol with privacy-preserving in Telecare medicine information system [J].
Chander, Bhanu ;
Gopalakrishnan, Kumaravelan .
COMPUTER COMMUNICATIONS, 2022, 191 :425-437
[6]   A secure and robust anonymous three-factor remote user authentication scheme for multi-server environment using ECC [J].
Chandrakar, Preeti ;
Om, Hari .
COMPUTER COMMUNICATIONS, 2017, 110 :26-34
[7]   Lightweight Anonymous Authentication Protocols for RFID Systems [J].
Chen, Min ;
Chen, Shigang ;
Fang, Yuguang .
IEEE-ACM TRANSACTIONS ON NETWORKING, 2017, 25 (03) :1475-1488
[8]   UHF-RFID-Based Real-Time Vehicle Localization in GPS-Less Environments [J].
Chen, Rui ;
Huang, Xiyuan ;
Zhou, Yan ;
Hui, Yilong ;
Cheng, Nan .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2022, 23 (07) :9286-9293
[9]   A Novel Spatial-Temporal Multi-Scale Alignment Graph Neural Network Security Model for Vehicles Prediction [J].
Diao, Chunyan ;
Zhang, Dafang ;
Liang, Wei ;
Li, Kuan-Ching ;
Hong, Yujie ;
Gaudiot, Jean-Luc .
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (01) :904-914
[10]   Secure attribute-based search in RFID-based inventory control systems [J].
Doss, Robin ;
Trujillo-Rasua, Rolando ;
Piramuthu, Selwyn .
DECISION SUPPORT SYSTEMS, 2020, 132