A differentially private square root unscented Kalman filter for protecting process parameters in ICPSs. (September 2020)

• Record Type: Journal Article
• Authors: Yuan, Jie; Wang, Yan; Ji, Zhicheng
• Is Part Of: ISA transactions. Volume 104(2020)
• Page Start: 44
• Page End: 52
• Publication Date: 2020-09
• Subjects: Industrial cyber–physical system -- Process parameter -- Differential privacy -- Privacy protection -- Square root unscented Kalman filter; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2019.12.010
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: Industrial cyber–physical systems (ICPSs) have received increasing attention from both academia and industry. However, the privacy-utility trade-off of process parameters is still a challenge in the ICPSs. To address this challenge, a Kalman filter-based differential privacy and an unscented Kalman filter-based differential privacy algorithms are derived. In order to increase the utility of process parameters while protecting the privacy of process parameters, a differentially private square root unscented Kalman filter algorithm is proposed by employing the square root unscented Kalman filter and differential privacy. The experiments based on a numerical control lathe are presented to prove the privacy and evaluate the utility of process parameters. Highlights: The privacy protection for process parameters in industrial cyber–physical systems. A Kalman filter-based differential privacy algorithm and its variant for comparison. A differentially private square root unscented Kalman filter algorithm is proposed.