Network APT Attack Detection Based on Big Data Analysis
In order to improve the security of the distributed optical fiber sensing network, the self-adaptive detection of the fiber sensing network needs to be carried out, and an overlap detection algorithm under the APT attack of the distributed optical fiber s
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Multimedia Technology and Enhanced Learning Second EAI International Conference, ICMTEL 2020 Leicester, UK, April 10–11, 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
Yu-Dong Zhang Shui-Hua Wang Shuai Liu (Eds.) •
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Multimedia Technology and Enhanced Learning Second EAI International Conference, ICMTEL 2020 Leicester, UK, April 10–11, 2020 Proceedings, Part I
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Editors Yu-Dong Zhang School of Informatics University of Leicester Leicestershire, UK
Shui-Hua Wang University of Leicester Leicestershire, UK
Shuai Liu Human Normal University Changsha, China
ISSN 1867-8211 ISSN 1867-822X (electronic) Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering ISBN 978-3-030-51099-2 ISBN 978-3-030-51100-5 (eBook) https://doi.org/10.1007/978-3-030-51100-5 © 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 warranty, express 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 jurisdiction
