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- Title
Security enhanced privacy-preserving data aggregation scheme for intelligent transportation system.
- Authors
Zuo, Kaizhong; Chu, Xixi; Hu, Peng; Ni, Tianjiao; Jin, Tingting; Chen, Fulong; Shen, Zhangyi
- Abstract
The intelligent transportation system can make traffic decisions through the sensory data collected by vehicles to ensure driving safety, improve traffic efficiency and traffic environment. Thus, the system has been widely concerned by industry and academia. However, the intelligent transportation system confronts several challenges in location privacy protection and data security during data aggregation. To solve these challenges, we propose a security-enhanced privacy-preserving data aggregation scheme for the intelligent transportation system, named SEPDA. Specifically, the SEPDA scheme utilizes the Chinese Remainder Theorem, Modified Paillier Cryptosystem and T-N Threshold Sharing to protect the location privacy and information security of vehicles, and obtains the mean and variance in the data report reading and analytics process. The SEPDA also uses the threshold cryptosystem to enhance the security of the traffic management center, which can avoid single-point attacks. Meanwhile, SEPDA employs batch authentication technology to reduce authentication overhead. Detailed security analysis and performance evaluation show that the SEPDA can resist various security threats and has low computational complexity, communication overhead and communication delay.
- Subjects
INTELLIGENT transportation systems; CHINESE remainder theorem; INFORMATION technology security; DATA security; DATA privacy; TRAFFIC safety
- Publication
Journal of Supercomputing, 2024, Vol 80, Issue 10, p13754
- ISSN
0920-8542
- Publication type
Article
- DOI
10.1007/s11227-024-05995-0