A novel user centric privacy mechanism in cyber physical system

Abstract

User-centric privacy preservation is of paramount importance in the realm of Cyber-Physical Systems (CPS), where making decisions based on nature of data is crucial. This abstract presents a novel approach to safeguarding user privacy within CPS environments by leveraging user query trends and dataset trends while incorporating the principles of differential privacy. By meticulously analyzing historical query patterns and dataset dynamics, this methodology empowers users to retain control over their sensitive data. The application of differential privacy techniques ensures that individual user information remains confidential while enabling comprehensive data analysis to unveil valuable insights, trends, and changes in data distribution. This approach fosters a dynamic privacy ecosystem where users can interact with CPS systems, query their data, and extract valuable knowledge, all while preserving their personal privacy. As we navigate the evolving landscape of CPS, characterized by increasing interconnectivity and data sharing, this user-centric privacy framework not only guarantees data protection but also ushers in a new era of responsible data-driven decision-making, where privacy and utility coexist harmoniously, ultimately enhancing the trust and confidence of users in the CPS environment.