\( P_{\alpha ,\beta } \) -Privacy: A Composable Formulation of Privacy Guarantees for Data Publishing Based on Permutati
Methods for Privacy-Preserving Data Publishing (PPDP) have been recently shown to be equivalent to essentially performing some permutations of the original data. This insight, called the permutation paradigm, establishes a common ground upon which any met
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Josep Domingo-Ferrer Krishnamurty Muralidhar (Eds.)
Privacy in Statistical Databases UNESCO Chair in Data Privacy, International Conference, PSD 2020 Tarragona, Spain, September 23–25, 2020 Proceedings
Lecture Notes in Computer Science Founding Editors Gerhard Goos Karlsruhe Institute of Technology, Karlsruhe, Germany Juris Hartmanis Cornell University, Ithaca, NY, USA
Editorial Board Members Elisa Bertino Purdue University, West Lafayette, IN, USA Wen Gao Peking University, Beijing, China Bernhard Steffen TU Dortmund University, Dortmund, Germany Gerhard Woeginger RWTH Aachen, Aachen, Germany Moti Yung Columbia University, New York, NY, USA
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More information about this series at http://www.springer.com/series/7409
Josep Domingo-Ferrer Krishnamurty Muralidhar (Eds.) •
Privacy in Statistical Databases UNESCO Chair in Data Privacy, International Conference, PSD 2020 Tarragona, Spain, September 23–25, 2020 Proceedings
123
Editors Josep Domingo-Ferrer Rovira i Virgili University Tarragona, Catalonia, Spain
Krishnamurty Muralidhar University of Oklahoma Norman, OK, USA
ISSN 0302-9743 ISSN 1611-3349 (electronic) Lecture Notes in Computer Science ISBN 978-3-030-57520-5 ISBN 978-3-030-57521-2 (eBook) https://doi.org/10.1007/978-3-030-57521-2 LNCS Sublibrary: SL3 – Information Systems and Applications, incl. Internet/Web, and HCI © Springer Nature Switzerland AG 2020 Chapter “Explaining Recurrent Machine Learning Models: Integral Privacy Revisited” is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/ by/4.0/). For further details see licence information in the chapter. This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzer
