Differentially private filtering

IEEE Transactions on Automatic Control

Volumn 59, Issue 2, 2014, Pages 341-354

  Le Ny, Jerome ^a   Pappas, George J ^b  

^a ÉCOLE POLYTECHNIQUE DE MONTRÉAL   (Canada)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

Estimation; filtering; Kalman filtering; privacy

Indexed keywords

DATA PRIVACY; ESTIMATION; FILTRATION; INTELLIGENT SYSTEMS;

DIFFERENTIAL PRIVACIES; END-USER APPLICATIONS; INTELLIGENT TRANSPORTATION SYSTEMS; KALMAN-FILTERING; MEASURED SIGNALS; PRIVACY CONCERNS; PRIVACY MECHANISMS; SIDE INFORMATION;

KALMAN FILTERS;

EID: 84893523202     PISSN: 00189286     EISSN: None     Source Type: Journal    
DOI: 10.1109/TAC.2013.2283096     Document Type: Article

References (42)

1. J. Le Ny and G. J. Pappas, Differentially private Kalman filtering, in Proc. 50th Annu. Allerton Conf. Commun., Control, Comput., Oct. 2012, pp. 1618-1625.
2. J. Le Ny and G. J. Pappas, Differentially private filtering, in Proc. Conf. Decision Control, Maui, HI, USA, Dec. 2012.
3. G. W. Hart, Nonintrusive appliance load monitoring, Proc. IEEE, vol. 80, no. 12, pp. 1870-1891, Dec. 1992.
4. A. Narayanan and V. Shmatikov, Robust de-anonymization of large sparse datasets (how to break anonymity of the Netflix Prize dataset), in Proc. IEEE Symp. Security and Privacy, 2008, pp. 111-125.
5. J. A. Calandrino, A. Kilzer, A. Narayanan, E. W. Felten, and V. Shmatikov, you might also like: Privacy risks of collaborative filtering, in Proc. IEEE Symp. Security Privacy, Berkeley, CA, USA, May 2011, pp. 231-246.
6. B. Hoh, T. Iwuchukwu, Q. Jacobson, M. Gruteser,A.Bayen, J.-C. Herrera, R. Herring, D.Work, M. Annavaram, and J.Ban, Enhancing privacy and accuracy in probe vehicle based traffic monitoring via virtual trip lines, IEEE Trans. Mobile Comput., vol. 11, no. 5, pp. 849-864, May 2012.
7. H. Zhang and J. Bolot, Anonymization of location data does not work: A large-scale measurement study, in Proc. 17th Annu. Int. Conf. Mobile Comput. and Network., 2011.
8. C. Dwork, F. McSherry, K. Nissim, and A. Smith, Calibrating noise to sensitivity in private data analysis, in Proc. 3rd Theory of Cryptogr. Conf., 2006, pp. 265-284. (Pubitemid 43979853)
9. S. P. Kasiviswanathan and A. Smith, A note on differential privacy: Defining resistance to arbitrary side information, 2008
10. [Online]. Available: http://arxiv.org/abs/0803.3946
11. C. Dwork, K. Kenthapadi, F. McSherry, I. M. M. Naor, and Naor, Our data, ourselves: Privacy via distributed noise generation, in Adv. Cryptol.-EUROCRYPT 06, 2006, pp. 486-503. (Pubitemid 44072257)
12. A. Roth, New algorithms for preserving differential privacy, Ph.D., Carnegie Mellon Univ., Pittsburgh, PA, USA, 2010.
13. C. Li, M. Hay, V. Rastogi, G. Miklau, and A. McGregor, Optimizing linear counting queries under differential privacy, in Principles of Database Syst. (PODS), 2010.
14. C. Dwork, M. Naor, T. Pitassi, and G. N. Rothblum, Differential privacy under continual observations, in Proc. ACM Symp. Theory Comput. (STOC), Cambridge, MA, USA, Jun. 2010.
15. T.-H. H. Chan, E. Shi, and D. Song, Private and continual release of statistics, ACM Trans. Info. Syst. Security, vol. 14, no. 3, pp. 26:1-26:24, Nov. 2011.
16. J. Bolot, N. Fawaz, S.Muthukrishnan, A. Nikolov, andN. Taft, Private decayed sum estimation under continual observation, 2011
17. [Online]. Available: http://arxiv.org/abs/1108.6123
18. Z. Huang, S. Mitra, and G. Dullerud, Differentially private iterative synchronous consensus, in Proc. CCS Workshop Privacy Electron. Soc. (WPES), Raleigh, NC, USA, Oct. 2012.
19. D. Varodayan and A. Khisti, Smartmeter privacy using a rechargeable battery:Minimizing the rate of information leakage, in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., Prag, Czech Republic, 2011, pp. 1932-1935.
20. L. Sankar, S. R. Rajagopalan, and H. V. Poor, A theory of privacy and utility in databases, Tech. Rep. Princeton Univ., Princeton, NJ, USA, 2011.
21. A. Blum, C. Dwork, F. McSherry, and K. Nissim, Practical privacy: The SuLQ framework, in Proc. 24th ACM SIGMOD-SIGACTSIGART Symp. Principles of Database Syst. (PODS), New York, NY, USA, 2005, pp. 128-138. (Pubitemid 43275476)
22. C. Dwork, Differential privacy, in Proc. 33rd Int. Colloq. Automata, Lang., Programm. (ICALP), 2006, vol. 4052, Lecture Notes in Computer Science.
23. L. Sweeney,-anonymity:A model for protecting privacy, Int. J. Uncertainty, Fuzziness, Knowl.-Based Syst., vol. 10, no. 05, pp. 557-570, 2002.
24. G. Duncan and D. Lambert, Disclosure-limited data dissemination, J. Amer. Statist. Associat., vol. 81, no. 393, pp. 10-28, Mar. 1986.
25. S. Gomatam, A. F. Karr, J. P. Reiter, and A. P. Sanil, Data dissemination and disclosure limitation in a world without microdata: A riskutility framework for remote access analysis servers, Statist. Sci., vol. 20, no. 2, pp. 163-177, 2005. (Pubitemid 41305192)
26. R. M. Dudley, Real Analysis and Probability, 2nd ed. Cambridge, U.K.: Cambridge Univ. Press, 2002.
27. F. McSherry and K. Talwar, Mechanism design via differential privacy, in Proc. IEEE Symp. Foundat. Comput. Sci., 2007, pp. 94-103.
28. T. M. Cover and J.A. Thomas, Elements of Information Theory. New York, NY, USA: Wiley, 1991.
29. L. Breiman, Probability. Philadelphia, PA, USA: SIAM, 1992, Classics in Appl. Math..
30. A. van der Schaft, L2-Gain and Passivity Techniques in Nonlinear Control. Berlin, Germany: Springer-Verlag, 2000.
31. E. Shi, T.-H H. Chan, E. Rieffel, R. Chow, and D. Song, Privacypreserving aggregation of time-series data, in Proc. 18th Annu. Netw. Distrib. Syst. Sec. Symp. (NDSS 11), Feb. 2011.
32. B. D. O. Anderson and J. B. Moore, Optimal Filtering. NewYork, NY, USA: Dover, 2005.
33. R. E. Skelton, T. Iwasaki, and K. Grigoriadis, A Unified Algebraic Approach to Linear Control Design. New York, NY, USA: Taylor & Francis, 1998.
34. C. Scherer, P. Gahinet, and M. Chilali, Multiobjective output-feedback control via LMI optimization, IEEE Trans. Autom. Control, vol. 42, no. 7, pp. 896-911, Jul. 1997. (Pubitemid 127826249)
35. C. W. Scherer, An efficient solution to multi-objective control problems with LMI objectives, Syst. Control Lett., vol. 40, pp. 43-57, 2000.
36. X. Sun, L. Munoz, and R. Horowitz, Mixture Kalman filter based highway congestion mode and vehicle density estimator and its application, in Proc. Amer. Control Conf., Jul. 2004, pp. 2098-2103.
37. M. Gruteser and D. Grunwald, Anonymous usage of location-based services through spatial and temporal cloaking, in Proc. 1st Int. Conf. Mobile Syst., Applicat. Services (MobiSys03), 2003, pp. 31-42.
38. R. Shokri, J. Freudiger, M. Jadliwala, and J.-P. Hubaux, A distortionbased metric for location privacy, in Proc. CCS Workshop Privacy Electron. Soc. (WPES), 2009.
39. R. Shokri, C. Troncoso, C. Diaz, J. Freudiger, and J.-P. Hubaux, Unraveling an old cloak-anonymity for location privacy, in Proc. CCS Workshop Privacy Electron. Soc. (WPES), 2010.
40. H. V. Poor, An Introduction to Signal Detection and Estimation, 2nd ed. New York, NY, USA: Springer, 1994.
41. J. Proakis, Digital Communications, 4th ed. New York, NY, USA: McGraw-Hill, 2000.
42. V. Rastogi and S. Nath, Differentially private aggregation of distributed time-series with transformation and encryption, in Proc. ACM Conf. Manage. Data (SIGMOD), Indianapolis, IN, USA, Jun. 2010.