System Design Approach for Control of Differentially Private Dynamical Systems
Abstract: This paper introduces a novel approach to concurrently design dynamic controllers and correlated differential privacy noise in dynamic control systems. An increase in privacy noise increases the system's privacy but adversely affects the system's performance. Our approach optimizes the noise distribution while shaping closed-loop system dynamics such that the privacy noise has the least impact on system performance and the most effect on system privacy. We further add privacy noise to both control input and system output to privatize the system's state for an adversary with access to both communication channels and direct output measurements. The study also suggests tailored privacy bounds for different states, providing a comprehensive framework for jointly optimizing system performance and privacy in the context of differential privacy.
- C. Dwork, A. Roth et al., “The algorithmic foundations of differential privacy,” Foundations and Trends® in Theoretical Computer Science, vol. 9, no. 3–4, pp. 211–407, 2014.
- C. Dwork, “Differential privacy: A survey of results,” in International conference on theory and applications of models of computation. Springer, 2008, pp. 1–19.
- S. Han and G. J. Pappas, “Privacy in control and dynamical systems,” Annual Review of Control, Robotics, and Autonomous Systems, vol. 1, pp. 309–332, 2018.
- K. Yazdani, A. Jones, K. Leahy, and M. Hale, “Differentially private lq control,” IEEE Transactions on Automatic Control, vol. 68, no. 2, pp. 1061–1068, 2022.
- M. U. Hassan, M. H. Rehmani, and J. Chen, “Differential privacy techniques for cyber physical systems: a survey,” IEEE Communications Surveys & Tutorials, vol. 22, no. 1, pp. 746–789, 2019.
- J. Le Ny and G. J. Pappas, “Differentially private filtering,” IEEE Transactions on Automatic Control, vol. 59, no. 2, pp. 341–354, 2013.
- C. Hawkins and M. Hale, “Differentially private formation control: Privacy and network co-design,” arXiv preprint arXiv:2205.13406, 2022.
- S. Han, U. Topcu, and G. J. Pappas, “Differentially private distributed constrained optimization,” IEEE Transactions on Automatic Control, vol. 62, no. 1, pp. 50–64, 2016.
- Y. Kawano and M. Cao, “Design of privacy-preserving dynamic controllers,” IEEE Transactions on Automatic Control, vol. 65, no. 9, pp. 3863–3878, 2020.
- Y. Kawano and M. Cao, “Differential privacy and qualitative privacy analysis for nonlinear dynamical systems,” IFAC-PapersOnLine, vol. 51, no. 23, pp. 52–57, 2018.
- C. Scherer, P. Gahinet, and M. Chilali, “Multiobjective output-feedback control via lmi optimization,” IEEE Transactions on Automatic Control, vol. 42, no. 7, pp. 896–911, 1997.
- R. Goyal, M. Majji, and R. E. Skelton, “Integrating structure, information architecture and control design: Application to tensegrity systems,” Mechanical Systems and Signal Processing, vol. 161, p. 107913, 2021.
- P. McDaniel and S. McLaughlin, “Security and privacy challenges in the smart grid,” IEEE Security & Privacy, vol. 7, no. 3, pp. 75–77, 2009.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.