A differentially private square root unscented Kalman filter for protecting process parameters in ICPSs
Jie Yuan1, Yan Wang1, Zhicheng Ji1
1School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, PR China.
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.
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