Vulnerability Characterization and Privacy Quantification for Cyber-Physical Systems

Abstract

Cyber-physical systems (CPS) data privacy protection during sharing, aggregating, and publishing is a challenging problem. Several privacy protection mechanisms have been developed in the literature to protect the sensitive data from adversarial analysis and eliminate the risk of re-identifying the original properties of shared data. However, most of the existing solutions have drawbacks, such as (i) lack of a proper vulnerability characterization model to accurately identify where privacy is needed, (ii) ignoring data providers privacy preference, (iii) using uniform privacy protection which may create inadequate privacy for some provider while overprotecting others, and (iv) lack of a comprehensive privacy quantification model assuring data privacy-preservation. To address these issues, we propose a personalized privacy preference framework by characterizing and quantifying the CPS vulnerabilities as well as ensuring privacy. First, we introduce a standard vulnerability profiling library (SVPL) by arranging the nodes of an energy-CPS from maximum to minimum vulnerable based on their privacy loss. Based on this model, we present our personalized privacy framework (PDP) in which Laplace noise is added based on the individual node's selected privacy preferences. Finally, combining these two proposed methods, we demonstrate that our privacy characterization and quantification model can attain better privacy preservation by eliminating the trade-off between privacy, utility, and risk of losing information.

A Survey on Privacy for B5G/6G: New Privacy Challenges, and Research Directions

“…Current work discuss on lack idea of privacy quantification approaches [76], [77], and it will be an important factor for B5G/6G to reach fully automated decision making regarding privacy aspects.…”

“…Also, [76] describes that it is unclear to assign coefficients a precise quantification for the importance of privacy in a smart home. The authors in [77] discuss the drawbacks of Cyber-physical Systems (CPS) data privacy, where they show that having data privacy characterization and quantification model help assuring privacy preservation. Still, such models are lacking at the moment.…”