A privacy-preserving multisubset data aggregation scheme with fault resilience for intelligent transportation system

ABSTRACT In Intelligent transportation system (ITS) applications, such as road safety and traffic monitoring, useful information is frequently gathered and transmitted to the management center for analysis, to provide a wide range of control, communication, and management measures. However, privacy of users must be preserved, since data transmitted by users may reveal sensitive private information such as location, travel route, etc. In this paper, we propose a privacy-preserving data aggregation scheme for ITS applications. The proposed scheme employs the combination of modified Paillier cryptosystem, Chinese Remainder theorem, Boneh short signature, and hash function operations not only to aggregate data of heterogeneous vehicles into one but also to provide fault resilience in a scenario when some devices are malfunctioning and not reporting to the management center. In the proposed scheme, each vehicle collects its data and computes a one-time secret key shared with the gateway to mask its data. We develop a hash function-based technique to ensure the authenticity and integrity of the aggregated encrypted data without revealing the individual data. Security analysis shows that the proposed scheme is secure, privacy-preserving, and supports conditional traceability. Extensive performance analysis and comparison demonstrate that the scheme is significantly more efficient than the related schemes.