Differential Privacy for Dynamic Data
This Springer brief provides the necessary foundations to understand differential privacy and describes practical algorithms enforcing this concept for the publication of real-time statistics based on sensitive data. Several scenarios of interest are cons
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Jerome Le Ny
Differential Privacy for Dynamic Data 123
SpringerBriefs in Electrical and Computer Engineering Control, Automation and Robotics
Series Editors Tamer Başar, Coordinated Science Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL, USA Miroslav Krstic, La Jolla, CA, USA
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Jerome Le Ny
Differential Privacy for Dynamic Data
123
Jerome Le Ny Department of Electrical Engineering Polytechnique Montréal Montreal, QC, Canada
ISSN 2191-8112 ISSN 2191-8120 (electronic) SpringerBriefs in Electrical and Computer Engineering ISSN 2192-6786 ISSN 2192-6794 (electronic) SpringerBriefs in Control, Automation and Robotics ISBN 978-3-030-41038-4 ISBN 978-3-030-41039-1 (eBook) https://doi.org/10.1007/978-3-030-41039-1 MATLAB is a registered trademark of The MathWorks, Inc. See mathworks.com/trademarks for a list
of additional trademarks. Mathematics Subject Classification (2010): 93E11, 93E10, 93A17, 68P30, 94A60 © The Author(s), under exclusive license to Springer Nature Switzerland AG 2020 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher,
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