IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v81y2022i2d10.1007_s11235-022-00911-4.html
   My bibliography  Save this article

A mutual authentication scheme in VANET providing vehicular anonymity and tracking

Author

Listed:
  • Jiabei He

    (Hunan University of Science and Technology)

  • Xuchong Liu

    (Hunan Police Academy)

  • Fan Wu

    (Xiamen Institute of Technology)

  • Chaoyang Chen

    (Hunan University of Science and Technology)

  • Xiong Li

    (University of Electronic Science and Technology of China)

Abstract

Nowadays, the intelligent transportation system (ITS) has developed prosperously all over the world. As a key technique in ITS, vehicular ad-hoc network (VANET) supports fast transmitting while bringing security problems simultaneously. To ensure efficiency, those unprotected data transmitting at a high speed can be easily eavesdropped on or forged, which will badly damage the ITS. To authenticate the identities of the vehicles in VANETs, signatures with certificates are often employed in historical research, but seldom study discusses the protection of generated data or mutual authentication between participants in VANETs. In order to tackle the problems above, we propose a new mutual authentication scheme for VANET where the private data can be kept away from attackers. In our scheme, the corresponding manager of each region can deal with the dynamic information of vehicles. The security analysis is also carried out and shown to emphasize the reliability of the scheme, such as anonymity, unlinkability and resistance to replay attacks, etc. Besides the resistance to different attacks, the real-time information secrecy can also be protected in our scheme, which is not achieved in the compared schemes. Moreover, the performance evaluation and simulation with NS-3 show that the packet delivery ratio reaches over 99% in most of the application scenarios, which proves that the scheme is efficient and practical.

Suggested Citation

  • Jiabei He & Xuchong Liu & Fan Wu & Chaoyang Chen & Xiong Li, 2022. "A mutual authentication scheme in VANET providing vehicular anonymity and tracking," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 81(2), pages 175-190, October.
  • Handle: RePEc:spr:telsys:v:81:y:2022:i:2:d:10.1007_s11235-022-00911-4
    DOI: 10.1007/s11235-022-00911-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-022-00911-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11235-022-00911-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kaffash, Sepideh & Nguyen, An Truong & Zhu, Joe, 2021. "Big data algorithms and applications in intelligent transportation system: A review and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 231(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ayelet Gal-Tzur & Sivan Albagli-Kim, 2023. "Systematic Analysis of the Literature Addressing the Use of Machine Learning Techniques in Transportation—A Methodology and Its Application," Sustainability, MDPI, vol. 16(1), pages 1-19, December.
    2. M. Azizur Rahman & Al-Amin Hossain & Binoy Debnath & Zinnat Mahmud Zefat & Mohammad Sarwar Morshed & Ziaul Haq Adnan, 2021. "Intelligent Vehicle Scheduling and Routing for a Chain of Retail Stores: A Case Study of Dhaka, Bangladesh," Logistics, MDPI, vol. 5(3), pages 1-21, September.
    3. Feng, Hailin & Lv, Haibin & Lv, Zhihan, 2023. "Resilience towarded Digital Twins to improve the adaptability of transportation systems," Transportation Research Part A: Policy and Practice, Elsevier, vol. 173(C).
    4. Qiang Shang & Yang Yu & Tian Xie, 2022. "A Hybrid Method for Traffic State Classification Using K-Medoids Clustering and Self-Tuning Spectral Clustering," Sustainability, MDPI, vol. 14(17), pages 1-20, September.
    5. Miguel F. Arevalo-Castiblanco & Jaime Pachon & Duvan Tellez-Castro & Eduardo Mojica-Nava, 2023. "Cooperative Cruise Control for Intelligent Connected Vehicles: A Bargaining Game Approach," Sustainability, MDPI, vol. 15(15), pages 1-21, August.
    6. Zhou, Chang & Li, Xiang & Chen, Lujie, 2023. "Modelling the effects of metro and bike-sharing cooperation: Cost-sharing mode vs information-sharing mode," International Journal of Production Economics, Elsevier, vol. 261(C).
    7. Karen Castañeda & Omar Sánchez & Rodrigo F. Herrera & Guillermo Mejía, 2022. "Highway Planning Trends: A Bibliometric Analysis," Sustainability, MDPI, vol. 14(9), pages 1-33, May.
    8. Qi, Quansong & Xu, Zhiyong & Rani, Pratibha, 2023. "Big data analytics challenges to implementing the intelligent Industrial Internet of Things (IIoT) systems in sustainable manufacturing operations," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
    9. Okkie Putriani & Sigit Priyanto & Imam Muthohar & Mukhammad Rizka Fahmi Amrozi, 2022. "Millimetre Wave and Sub-6 5G Readiness of Mobile Network Big Data for Public Transport Planning," Sustainability, MDPI, vol. 15(1), pages 1-19, December.
    10. Pan, Hongye & Qi, Lingfei & Zhang, Zutao & Yan, Jinyue, 2021. "Kinetic energy harvesting technologies for applications in land transportation: A comprehensive review," Applied Energy, Elsevier, vol. 286(C).
    11. Muxia Yao & Bin Yao & Jeremy Cenci & Chenyang Liao & Jiazhen Zhang, 2023. "Visualisation of High-Density City Research Evolution, Trends, and Outlook in the 21st Century," Land, MDPI, vol. 12(2), pages 1-27, February.
    12. Wei, Sen & Li, Yanping & Yang, Hanqing & Xie, Minghui & Wang, Yuanqing, 2023. "A comprehensive operation and maintenance assessment for intelligent highways: A case study in Hong Kong-Zhuhai-Macao bridge," Transport Policy, Elsevier, vol. 142(C), pages 84-98.
    13. Yang He & Lisheng Jin & Huanhuan Wang & Zhen Huo & Guangqi Wang & Xinyu Sun, 2022. "Automatic ROI Setting Method Based on LSC for a Traffic Congestion Area," Sustainability, MDPI, vol. 14(23), pages 1-19, December.
    14. P. V. Thayyib & Rajesh Mamilla & Mohsin Khan & Humaira Fatima & Mohd Asim & Imran Anwar & M. K. Shamsudheen & Mohd Asif Khan, 2023. "State-of-the-Art of Artificial Intelligence and Big Data Analytics Reviews in Five Different Domains: A Bibliometric Summary," Sustainability, MDPI, vol. 15(5), pages 1-38, February.
    15. Alaa Amin Abdalla & Yousif Abdelbagi Abdalla & Akarm M. Haddad & Ganga Bhavani & Eman Zabalawi, 2022. "Connections between Big Data and Smart Cities from the Supply Chain Perspective: Understanding the Impact of Big Data," Sustainability, MDPI, vol. 14(23), pages 1-13, December.
    16. Chung, Sai-Ho, 2021. "Applications of smart technologies in logistics and transport: A review," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 153(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:telsys:v:81:y:2022:i:2:d:10.1007_s11235-022-00911-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.