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Big Data Analytics with Applications in Insider Threat Detection
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Today's malware mutates randomly to avoid detection, but reactively adaptive malware is more intelligent, learning and adapting to new computer defenses on the fly. Using the same algorithms that antivirus software uses to detect viruses, reactively adaptive malware deploys those algorithms to outwit antivirus defenses and to go undetected. This book provides details of the tools, the types of malware the tools will detect, implementation of the tools in a cloud computing framework and the applications for insider threat detection
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www.crcpress.com
Cyber Security
The significant developments in data management and analytics, web services, cloud
computing, and cyber security have evolved into an area called big data management and
analytics (BDMA) as well as big data security and privacy (BDSP).
Big Data Analytics with Applications in Insider Threat Detection explores big data an-
alytics techniques and applies them for cyber security including insider threat detection.
It discusses various concepts, technologies, issues, and challenges for both BDMA and
BDSP. In addition, it also presents several of the experimental systems in cloud comput-
ing and secure cloud computing that were designed and developed at The University of
Texas at Dallas.
Big Data Analytics with Applications in Insider Threat Detection reviews the devel-
opments in topics both BDMA and BDSP and discuss the issues and challenges in se-
curing big data as well as applying big data techniques to solve problems. There is also a
focused section on the big data analytics technique called stream data mining as well as
approaches to applying this technique to insider threat detection.
Divided into five parts, each describing some aspect of the technology that is relevant to
BDMA and BSDP, the major focus of this book is on stream data analytics and its appli-
cations in insider threat detection.
Part I describes supporting technologies for BDMA and BDSP including data security
and privacy, data mining, cloud computing, and semantic web.
Part II provides a detailed overview of the techniques developed for stream data analytics.
In particular, it describes techniques on novel class detection for data streams.
Part III discusses the applications of stream analytics for insider threat detection.
Part IV discusses some of the experimental systems developed based on BDMA and
BDSP, including secure query processing for big data as well as social media analysis.
Part V discusses some of the challenges for BDMA and BDSP, especially securing
the Internet of Things and plans for developing experimental infrastructures for BDMA
and BDSP.
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an informa business
www.crcpress.com
ISBN: 978-1-4987-0547-9
9 781498 705479
90000
K24769
Big Data Analytics with
Applications in Insider
Threat Detection
Big Data Analytics with Applications
in Insider Threat Detection
Bhavani Thuraisingham • Pallabi Parveen
Mehedy Masud •Latifur Khan
Thuraisingham
Parveen
Masud • Khan
K24769 cvr mech.indd 1 11/3/17 8:57 AM
Big Data Analytics with
Applications in Insider
Threat Detection
Big Data Analytics with
Applications in Insider
Threat Detection
Bhavani Thuraisingham
Mohammad Mehedy Masud
Pallabi Parveen
Latifur Khan
CRC Press
Taylor & Francis Group
6000 Broken Sound Parkway NW, Suite 300
Boca Raton, FL 33487-2742
© 2018 by Taylor & Francis Group, LLC
CRC Press is an imprint of Taylor & Francis Group, an Informa business
No claim to original U.S. Government works
Printed on acid-free paper
International Standard Book Number-13: 978-1-4987-0547-9 (Hardback)
This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been
made to publish reliable data and information, but the author and publisher cannot assume responsibility for the
validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the
copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to
publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let
us know so we may rectify in any future reprint.
Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or
utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including pho-
tocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission
from the publishers.
For permission to photocopy or use material electronically from this work, please access www.copyright.com (http://
www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA
01923, 978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users.
For organizations that have been granted a photocopy license by the CCC, a separate system of payment has been
arranged.
Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for
identification and explanation without intent to infringe.
Library of Congress Cataloging-in-Publication Data
Names: Parveen, Pallabi, author.
Title: Big data analytics with applications in insider threat detection /
Pallabi Parveen, Bhavani Thuraisingham, Mohammad Mehedy Masud, Latifur Khan.
Description: Boca Raton : Taylor & Francis, CRC Press, 2017. | Includes bibliographical references.
Identifiers: LCCN 2017037808 | ISBN 9781498705479 (hb : alk. paper)
Subjects: LCSH: Computer security--Data processing. | Malware (Computer software) | Big data. |
Computer crimes--Investigation. | Computer networks--Access control.
Classification: LCC QA76.9.A25 P384 2017 | DDC 005.8--dc23
LC record available at https://lccn.loc.gov/2017037808
Visit the Taylor & Francis Web site at
http://www.taylorandfrancis.com
and the CRC Press Web site at
http://www.crcpress.com
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