Anomaly Detection on Web-User Behaviors Through Deep Learning

The modern Internet has witnessed the proliferation of web applications that play a crucial role in the branding process among enterprises. Web applications provide a communication channel between potential customers and business products. However, web ap

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ty and Privacy in Communication Networks 16th EAI International Conference, SecureComm 2020 Washington, DC, USA, October 21–23, 2020 Proceedings, Part I

Part 1

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering Editorial Board Members Ozgur Akan Middle East Technical University, Ankara, Turkey Paolo Bellavista University of Bologna, Bologna, Italy Jiannong Cao Hong Kong Polytechnic University, Hong Kong, China Geoffrey Coulson Lancaster University, Lancaster, UK Falko Dressler University of Erlangen, Erlangen, Germany Domenico Ferrari Università Cattolica Piacenza, Piacenza, Italy Mario Gerla UCLA, Los Angeles, USA Hisashi Kobayashi Princeton University, Princeton, USA Sergio Palazzo University of Catania, Catania, Italy Sartaj Sahni University of Florida, Gainesville, USA Xuemin (Sherman) Shen University of Waterloo, Waterloo, Canada Mircea Stan University of Virginia, Charlottesville, USA Xiaohua Jia City University of Hong Kong, Kowloon, Hong Kong Albert Y. Zomaya University of Sydney, Sydney, Australia

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More information about this series at http://www.springer.com/series/8197

Noseong Park Kun Sun Sara Foresti Kevin Butler Nitesh Saxena (Eds.) •







Security and Privacy in Communication Networks 16th EAI International Conference, SecureComm 2020 Washington, DC, USA, October 21–23, 2020 Proceedings, Part I

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Editors Noseong Park Yonsei University Seoul, Korea (Republic of) Sara Foresti Dipartimento di Informatica Universita degli Studi Milan, Milano, Italy

Kun Sun George Mason University Fairfax, VA, USA Kevin Butler University of Florida Gainesville, FL, USA

Nitesh Saxena Division of Nephrology University of Alabama Birmingham, AL, USA

ISSN 1867-8211 ISSN 1867-822X (electronic) Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN 978-3-030-63085-0 ISBN 978-3-030-63086-7 (eBook) https://doi.org/10.1007/978-3-030-63086-7 © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 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 authors or the editors give a war