A Survey of the Social Internet of Vehicles: Secure Data Issues, Solutions, and Federated Learning

The Social Internet of Vehicles (SIoV) is constructed so that the vehicle, as an entity, generates social awareness, which leads to the social behavior of the vehicle. The SIoV has multidimensional, heterogeneous, massive, real-time dynamic data, so its data security is a major concern. The structure of the SIoV and the characteristics of security primitives are studied in this review, which defines the social community by the vehicle. After this, the attack model is elaborated on, further refining the source, target, and capabilities of the attack. On this basis, typical data security solutions are compared and analyzed. In this survey, the focus is on the collaborative application of federated learning in SIoV data security protection. Ultimately, the current challenges and possible future research directions in this field are discussed.

• Record URL:
  http://dx.doi.org/10.1109/MITS.2022.3190036
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/19391390
• Supplemental Notes:
  • Copyright © 2023, IEEE.
• Authors:
  • Xing, Ling
  • Zhao, Pengcheng
  • Gao, Jianping
  • Wu, Honghai
  • 0000-0001-7169-313X
• Publication Date: 2023-3

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References;
• Pagination: pp 70-84
• Serial:
  • IEEE Intelligent Transportation Systems Magazine
  • Volume: 15
  • Issue Number: 2
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 1939-1390
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5117645

Subject/Index Terms

• TRT Terms: Computer security; Decentralization; Internet of things; Machine learning; Social media; Vehicle dynamics
• Subject Areas: Data and Information Technology; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01897719
• Record Type: Publication
• Files: TRIS
• Created Date: Oct 27 2023 1:37PM