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Published in:
Defining Privacy-Preserving Data Analysis Read chapter Read first chapter

2020 | OriginalPaper | Chapter

4. Differentially Private Filtering for Stationary Stochastic Collective Signals

Author : Jerome Le Ny

Published in: Differential Privacy for Dynamic Data

Publisher: Springer International Publishing

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Abstract

This chapter builds on the two-stage architecture for differentially private filtering, and presents mechanisms with better performance than the zero-forcing equalization mechanism, for the situation where we have some knowledge about the statistics of the privacy-sensitive input signals, which moreover are assumed to be stationary. The mechanisms described use as second stage in the architecture a Wiener filter, and the performance of the overall mechanism is then optimized, following the general methodology outlined in Chap. 3.

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previous chapter A Two-Stage Architecture for Differentially Private Filtering
next chapter Differentially Private Kalman Filtering
Footnotes
1
Some of the text in Sect. 4.3 of this chapter is reprinted, with permission, from Le Ny and Mohammady (2018) (© [2018] IEEE).
 
Literature
Boyd S et al (1994) Linear matrix inequalities in system and control theory. Studies in applied mathematics. SIAM, Philadelphia
Kailath T, Sayed AH, Hassibi B (2000) Linear estimation. Prentice Hall, Upper Saddle RiverMATH
Le Ny J, Mohammady M (2018) Differentially private MIMO filtering for event streams. IEEE Trans Autom Control 63(1):145–157MathSciNetCrossRef
Palomar DP, Fonollosa JR (2005) Practical algorithms for a family of waterfilling solutions. IEEE Trans Signal Process 53(2):686–695MathSciNetCrossRef
Proakis J (2000) Digital communications, 4th edn. McGraw-Hill, New YorkMATH
Salz J (1985) Digital transmission over cross-coupled linear channels. AT&T Tech J 64(6):1147–1159CrossRef
Yang J, Roy S (1994) On joint transmitter and receiver optimization for multiple-input-multiple-output (MIMO) transmission systems. IEEE J Commun 42(12):3221–3231CrossRef
Metadata
Title
Differentially Private Filtering for Stationary Stochastic Collective Signals
Author
Jerome Le Ny
Copyright Year
2020
Book
Differential Privacy for Dynamic Data

Print ISBN: 978-3-030-41038-4

Electronic ISBN: 978-3-030-41039-1

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-41039-1_4