Part I: Statistical Data Privacy - 1. Fisher Information Privacy with Application to Smart Meter Privacy Using HVAC Units.- 2. Smart Meter Privacy.- 3. Privacy Against Adversarial Hypothesis Testing: Theory and Application to Smart Meter Privacy Problem.- 4. Statistical Parameter Privacy.- 5. Privacy Verification and Enforcement via Belief Manipulation.- 6. Information-Theoretic Privacy through Chaos Synchronization and Optimal Additive Noise.- 7. Differentially Provate Analysis of Transportation Data.- 8. On the Role of Cooperation in Private Multi-agent Systems.- Part II: Encryption-Based Privacy - 9. Secure Multi-party Computation for Cloud-based Control.- 10. Comprehensive Introduction to Fully Homomorphic Encryption for Dynamic Feedback Controller via LWE-based Cryptosystem. 11. Encrypted Model Predictive Control in the Cloud.- 12. Encrypted Control Using Multiplicative Homomorphic Encryption.
Farhad Farokhi is a Research Scientist at the Information Security and Privacy Group at CSIRO's Data61 and a Research Fellow at the Department of Electrical and Electronic Engineering at the University of Melbourne. In 2014, he received his PhD degree in Automatic Control from KTH Royal Institute of Technology, Sweden. During his PhD studies, he was a visiting researcher at the University of California at Berkeley and the University of Illinois at Urbana-Champaign. Farhad has been the recipient of the VESKI Victoria Fellowship from the Victorian State Government as well as the McKenzie Fellow and the 2015 Early Career Researcher Award from the University of Melbourne. He was a finalist in the 2014 European Embedded Control Institute (EECI) PhD Award. He has been part of numerous projects on data privacy and cyber-security funded by the Defence Science and Technology Group, the Department of the Prime Minister and Cabinet, the Department of Environment and Energy, and CSIRO in Australia. His research interests include security and privacy in cyber-physical systems, such as smart grids and intelligent transportation systems.
This book addresses privacy in dynamical systems, with applications to smart metering, traffic estimation, and building management. In the first part, the book explores statistical methods for privacy preservation from the areas of differential privacy and information-theoretic privacy (e.g., using privacy metrics motivated by mutual information, relative entropy, and Fisher information) with provable guarantees. In the second part, it investigates the use of homomorphic encryption for the implementation of control laws over encrypted numbers to support the development of fully secure remote estimation and control. Chiefly intended for graduate students and researchers, the book provides an essential overview of the latest developments in privacy-aware design for dynamical systems.