Abstract
In this chapter, we use Heating, Ventilation, and Air Conditioning (HVAC) units to preserve the privacy of households with smart meters in addition to regulating indoor temperature. We model the effect of the HVAC unit as an additive noise in the household consumption. The Cramér-Rao bound is used to relate the inverse of the trace of the Fisher information matrix to the quality of an adversary’s estimation error of the household private consumption from the aggregate consumption of the household with the HVAC unit. This establishes the Fisher information as the measure of privacy leakage. We compute the optimal privacy-preserving policy for controlling the HVAC unit through minimizing a weighted sum of the Fisher information and the cost operating the HVAC unit. The optimization problem also contains the constraints on the temperatures of the house.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Ács G, Castelluccia C (2011) I have a DREAM! (DiffeRentially privatE smArt Metering). In: Filler T, Pevný T, Craver S, Ker A (eds) Information Hiding: 13th International Conference, IH 2011, Prague, Czech Republic, May 18–20, 2011, Revised Selected Papers. Springer, Berlin, pp 118–132
Bambauer J, Muralidhar K, Sarathy R (2013) Fool’s gold: an illustrated critique of differential privacy. Vanderbilt J Entertain Technol Law 16:701
Dwork C (2008) Differential privacy: a survey of results. In: Agrawal M, Du D, Duan Z, Li A (eds) 5th Proceedings of international conference theory and applications of models of computation, TAMC 2008, Xi’an, China, 25–29 April 2008, pp. 1–19. Springer, Berlin
Dwork C (2011) Differential privacy. In: van Tilborg HCA, Jajodia S (eds) Encyclopedia of Cryptography and Security. Springer, US, Boston, MA
Edwards CH (1973) Advanced Calculus of Several Variables. Academic Press
Farokhi F (2019) Development and analysis of deterministic privacy-preserving policies using non-stochastic information theory. IEEE Trans Inf Forensics Secur 14(10):2567–2576
Farokhi F, Milosevic J, Sandberg H (2016) Optimal state estimation with measurements corrupted by Laplace noise. In: Proceedings of the 55th IEEE conference on decision and control
Farokhi F, Sandberg H (2018) Fisher information as a measure of privacy: preserving privacy of households with smart meters using batteries. IEEE Trans Smart Grid 9(5):4726–4734
Farokhi F, Sandberg H (2019) Ensuring privacy with constrained additive noise by minimizing Fisher information. Automatica 99:275–288
Garfinkel SL, Abowd JM, Powazek S (2018) Issues encountered deploying differential privacy. In: Proceedings of the 2018 workshop on privacy in the electronic society, pp 133–137
Greenberg A (2017) How one of apple’s key privacy safeguards falls short. https://www.wired.com/story/apple-differential-privacy-shortcomings/
Haeberlen A, Pierce BC, Narayan A (2011) Differential privacy under fire. In: USENIX security symposium
Han S, Topcu U, Pappas GJ (2014) Differentially private convex optimization with piecewise affine objectives. In: Proceedings of the 53rd IEEE conference on decision and control, pp 2160–2166
Hart GW (1989) Residential energy monitoring and computerized surveillance via utility power flows. IEEE Technol Soc Mag 8(2):12–16
Huang Z, Wang Y, Mitra S, Dullerud GE (2014) On the cost of differential privacy in distributed control systems. In: Proceedings of the 3rd international conference on high confidence networked systems, pp 105–114
Jeyakumar V, Wolkowicz H (1990) Zero duality gaps in infinite-dimensional programming. J Optim Theory Appl 67(1):87–108
Le Ny J, Pappas GJ (2014) Differentially private filtering. IEEE Trans Autom Control 59(2):341–354
Liang Y, Poor HV, Shamai S (2009) Information theoretic security. Found Trends® Commun Inf Theory 5(4–5), 355–580
McDaniel P, McLaughlin S (2009) Security and privacy challenges in the smart grid. IEEE Secur Priv 7(3):75–77
Muralidhar K, Sarathy R (2010) Does differential privacy protect terry gross’ privacy? In: Domingo-Ferrer J, Magkos E (eds) Privacy in statistical databases. Springer, Berlin, pp 200–209
Sandberg H, Dán G, Thobaben R (2015) Differentially private state estimation in distribution networks with smart meters. In: Proceedings of the 54th IEEE conference on decision and control, pp 4492–4498
Shao J (2003) Mathematical Statistics. Springer Texts in Statistics. Springer, New York
Tang J, Korolova A, Bai X, Wang X, Wang X (2017) Privacy loss in Apple’s implementation of differential privacy on macos 10.12. arXiv preprint arXiv:1709.02753
Wyner AD (1975) The wire-tap channel. Bell Syst Tech J 54(8):1355–1387
Yamamoto H (1983) A source coding problem for sources with additional outputs to keep secret from the receiver or wiretappers. IEEE Trans Inf Theory 29(6):918–923
Zoha A, Gluhak A, Imran MA, Rajasegarar S (2012) Non-intrusive load monitoring approaches for disaggregated energy sensing: a survey. Sensors 12(12):16838–16866
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Farokhi, F., Sandberg, H. (2020). Fisher Information Privacy with Application to Smart Meter Privacy Using HVAC Units. In: Farokhi, F. (eds) Privacy in Dynamical Systems. Springer, Singapore. https://doi.org/10.1007/978-981-15-0493-8_1
Download citation
DOI: https://doi.org/10.1007/978-981-15-0493-8_1
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-0492-1
Online ISBN: 978-981-15-0493-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)