Variational Optimization of Informational Privacy
The datasets containing sensitive information can’t be publicly shared as a privacy-risk posed by several types of attacks exists. The data perturbation approach uses a random noise adding mechanism to preserve privacy, however, results in distortion of u
- PDF / 8,042,643 Bytes
- 120 Pages / 439.37 x 666.142 pts Page_size
- 17 Downloads / 242 Views
rt Systems Applications DEXA 2020 International Workshops BIOKDD, IWCFS and MLKgraphs Bratislava, Slovakia, September 14–17, 2020 Proceedings
Communications in Computer and Information Science Commenced Publication in 2007 Founding and Former Series Editors: Simone Diniz Junqueira Barbosa, Phoebe Chen, Alfredo Cuzzocrea, Xiaoyong Du, Orhun Kara, Ting Liu, Krishna M. Sivalingam, Dominik Ślęzak, Takashi Washio, Xiaokang Yang, and Junsong Yuan
Editorial Board Members Joaquim Filipe Polytechnic Institute of Setúbal, Setúbal, Portugal Ashish Ghosh Indian Statistical Institute, Kolkata, India Igor Kotenko St. Petersburg Institute for Informatics and Automation of the Russian Academy of Sciences, St. Petersburg, Russia Raquel Oliveira Prates Federal University of Minas Gerais (UFMG), Belo Horizonte, Brazil Lizhu Zhou Tsinghua University, Beijing, China
1285
More information about this series at http://www.springer.com/series/7899
Gabriele Kotsis A Min Tjoa Ismail Khalil Lukas Fischer Bernhard Moser Atif Mashkoor Johannes Sametinger Anna Fensel Jorge Martinez-Gil (Eds.) •
•
•
•
•
•
•
•
Database and Expert Systems Applications DEXA 2020 International Workshops BIOKDD, IWCFS and MLKgraphs Bratislava, Slovakia, September 14–17, 2020 Proceedings
123
Editors Gabriele Kotsis Johannes Kepler University of Linz Linz, Austria
A Min Tjoa Vienna University of Technology Vienna, Wien, Austria
Ismail Khalil Johannes Kepler University of Linz Linz, Oberösterreich, Austria
Lukas Fischer Software Competence Center Hagenberg Linz, Austria
Bernhard Moser Software Competence Center Hagenberg Linz, Austria
Atif Mashkoor Software Competence Center Hagenberg Linz, Austria
Johannes Sametinger Johannes Kepler University of Linz Linz, Austria
Anna Fensel University of Innsbruck Innsbruck, Tirol, Austria
Jorge Martinez-Gil Software Competence Center Hagenberg Linz, Austria
ISSN 1865-0929 ISSN 1865-0937 (electronic) Communications in Computer and Information Science ISBN 978-3-030-59027-7 ISBN 978-3-030-59028-4 (eBook) https://doi.org/10.1007/978-3-030-59028-4 © Springer Nature Switzerland AG 2020 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
Data Loading...
