Deep Learning Innovations and Their Convergence With Big Data (Advances in Data Mining and Database Management

288 Pages·2017·8.297 MB·English

by  S. Karthik, S. Karthik, Anand Paul, N. Karthikeyan

Deep Learning
Innovations and Their
Convergence With Big
Data
S. Karthik
SNS College of Technology, Anna University, India
Anand Paul
Kyungpook National University, South Korea
N. Karthikeyan
Mizan-Tepi University, Ethiopia
A volume in the Advances in Data
Mining and Database Management
(ADMDM) Book Series
Published in the United States of America by
IGI Global
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Library of Congress Cataloging-in-Publication Data
Names: Karthik, S., 1977- editor. | Paul, Anand, editor. | Karthikeyan, N.,
1977- editor.
Title: Deep learning innovations and their convergence with big data / S.
Karthik, Anand Paul, and N. Karthikeyan, editors.
Description: Hershey, PA : Information Science Reference, [2018] | Includes
bibliographical references.
Identifiers: LCCN 2017011947| ISBN 9781522530152 (hardcover) | ISBN
9781522530169 (ebook)
Subjects: LCSH: Machine learning--Technological innovations. | Big data.
Classification: LCC Q325.5 .D44 2018 | DDC 006.3/1--dc23 LC record available at https://lccn.loc.
gov/2017011947

This book is published in the IGI Global book series Advances in Data Mining and Database
Management (ADMDM) (ISSN: 2327-1981; eISSN: 2327-199X)
British Cataloguing in Publication Data
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All work contributed to this book is new, previously-unpublished material.
The views expressed in this book are those of the authors, but not necessarily of the publisher.
For electronic access to this publication, please contact: [email protected].
Advances in Data Mining
and Database Management
(ADMDM) Book Series
ISSN:2327-1981
EISSN:2327-199X
Editor-in-Chief: David Taniar, Monash University, Australia
Mission
With the large amounts of information available to organizations in today’s digital
world, there is a need for continual research surrounding emerging methods and
tools for collecting, analyzing, and storing data.
The Advances in Data Mining & Database Management (ADMDM) series aims
to bring together research in information retrieval, data analysis, data warehousing,
and related areas in order to become an ideal resource for those working and studying
in these fields. IT professionals, software engineers, academicians and upper-level
students will find titles within the ADMDM book series particularly useful for
staying up-to-date on emerging research, theories, and applications in the fields of
data mining and database management.
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Titles in this Series
For a list of additional titles in this series, please visit:
https://www.igi-global.com/book-series/advances-data-mining-database-management/37146
Data Visualization and Statistical Literacy for Open and Big Data
Theodosia Prodromou (University of New England, Australia)
Information Science Reference • ©2017 • 365pp • H/C (ISBN: 9781522525127) • US $205.00
Web Semantics for Textual and Visual Information Retrieval
Aarti Singh (Guru Nanak Girls College, Yamuna Nagar, India) Nilanjan Dey (Techno India
College of Technology, India) Amira S. Ashour (Tanta University, Egypt & Taif University,
Saudi Arabia) and V. Santhi (VIT University, India)
Information Science Reference • ©2017 • 290pp • H/C (ISBN: 9781522524830) • US $185.00
Advancing Cloud Database Systems and Capacity Planning With Dynamic Applications
Narendra Kumar Kamila (C.V. Raman College of Engineering, India)
Information Science Reference • ©2017 • 430pp • H/C (ISBN: 9781522520139) • US $210.00
Web Data Mining and the Development of Knowledge-Based Decision Support Systems
G. Sreedhar (Rashtriya Sanskrit Vidyapeetha (Deemed University), India)
Information Science Reference • ©2017 • 409pp • H/C (ISBN: 9781522518778) • US $165.00
Intelligent Multidimensional Data Clustering and Analysis
Siddhartha Bhattacharyya (RCC Institute of Information Technology, India) Sourav De (Cooch
Behar Government Engineering College, India) Indrajit Pan (RCC Institute of Information
Technology, India) and Paramartha Dutta (Visva-Bharati University, India)
Information Science Reference • ©2017 • 450pp • H/C (ISBN: 9781522517764) • US $210.00
Emerging Trends in the Development and Application of Composite Indicators
Veljko Jeremic (University of Belgrade, Serbia) Zoran Radojicic (University of Belgrade,
Serbia) and Marina Dobrota (University of Belgrade, Serbia)
Information Science Reference • ©2017 • 402pp • H/C (ISBN: 9781522507147) • US $205.00
Web Usage Mining Techniques and Applications Across Industries
A.V. Senthil Kumar (Hindusthan College of Arts and Science, India)
Information Science Reference • ©2017 • 424pp • H/C (ISBN: 9781522506133) • US $200.00
For an enitre list of titles in this series, please visit:
https://www.igi-global.com/book-series/advances-data-mining-database-management/37146
701 East Chocolate Avenue, Hershey, PA 17033, USA
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Editorial Advisory Board
Syed M. Bukhari, King Abdulaziz University, Saudi Arabia
Xiao-Zhi Gao, Aalto University, Finland
Heba A. Hassen, Dhofar University, Oman
Dilip Malai, Mekelle University, Ethiopia
Sigurd Meldal, San Jose State University, USA
Vijay Singh Rathore, Rajasthan Institute of Engineering and Technology, India
Jung Soon-Ki, Kyungpook National University, South Korea
Lipo Way, Nanyang Technological University, Singapore
Ahmed F. Zobaa, Brunel University, UK
List of Reviewers
A. S. N. Chakravarthy, JNTU, India
T. Hanumanthappa, Bangalore University, India
T. Senthil Kumar, Amrita Vishwa VidhyaPeetham, India
Palaniswamy, Government College of Engineering Tamilnadu, India
Madhan Kumar Srinivasan, Global Science and Technology, Singapore
Table of Contents
Preface..................................................................................................................xv
Acknowledgment...............................................................................................xxii
Chapter 1
Advanced.Threat.Detection.Based.on.Big.Data.Technologies...............................1
Madhvaraj M. Shetty, Mangalore University, India
Manjaiah D. H., Mangalore University, India
Chapter 2
A.Brief.Review.on.Deep.Learning.and.Types.of.Implementation.for.Deep.
Learning................................................................................................................20
Uthra Kunathur Thikshaja, Kyungpook National University, South
Korea
Anand Paul, Kyungpook National University, South Korea
Chapter 3
Big.Spectrum.Data.and.Deep.Learning.Techniques.for.Cognitive.Wireless.
Networks...............................................................................................................33
Punam Dutta Choudhury, Gauhati University, India
Ankumoni Bora, Gauhati University, India
Kandarpa Kumar Sarma, Gauhati University, India
Chapter 4
Efficiently.Processing.Big.Data.in.Real-Time.Employing.Deep.Learning.
Algorithms............................................................................................................61
Murad Khan, Sarhad University of Science and Information Technology,
Pakistan
Bhagya Nathali Silva, Kyungpook National University, South Korea
Kijun Han, Kyungpook National University, South Korea

Chapter 5
Digital.Investigation.of.Cybercrimes.Based.on.Big.Data.Analytics.Using.
Deep.Learning.......................................................................................................79
Ezz El-Din Hemdan, Managlore University, India
Manjaiah D. H., Mangalore University, India
Chapter 6
Classifying.Images.of.Drought-Affected.Area.Using.Deep.Belief.Network,.
kNN,.and.Random.Forest.Learning.Techniques.................................................102
Sanjiban Sekhar Roy, VIT University, India
Pulkit Kulshrestha, VIT University, India
Pijush Samui, NIT Patna, India
Chapter 7
Big.Data.Deep.Analytics.for.Geosocial.Networks..............................................120
Muhammad Mazhar Ullah Rathore, Kyungpook National University,
South Korea
Awais Ahmad, Yeungnam University, South Korea
Anand Paul, Kyungpook National University, South Korea
Chapter 8
Data.Science:.Recent.Developments.and.Future.Insights:.................................141
Sabitha Rajagopal, SNS College of Technology, Anna University, India
Chapter 9
Data.Science.and.Computational.Biology..........................................................152
Singaraju Jyothi, Sri Padmavati Mahila University, India
Bhargavi P, Sri Padmavati Mahila University, India
Chapter 10
After.Cloud:.In.Hypothetical.World...................................................................173
Shigeki Sugiyama, Independent Researcher, Japan
Chapter 11
Cloud-Based.Big.Data.Analytics.in.Smart.Educational.System........................189
Newlin Rajkumar Manokaran, Anna University – Coimbatore, India
Venkatesa Kumar Varathan, Anna University – Coimbatore, India
Shalinie Deepak, United Institute of Technology, India

Related References............................................................................................200
Compilation of References...............................................................................237
About the Contributors....................................................................................256
Index...................................................................................................................263
Detailed Table of Contents
Preface..................................................................................................................xv
Acknowledgment...............................................................................................xxii
Chapter 1
Advanced.Threat.Detection.Based.on.Big.Data.Technologies...............................1
Madhvaraj M. Shetty, Mangalore University, India
Manjaiah D. H., Mangalore University, India
Today.constant.increase.in.number.of.cyber.threats.apparently.shows.that.current.
countermeasures.are.not.enough.to.defend.it..With.the.help.of.huge.generated.
data,.big.data.brings.transformative.potential.for.various.sectors..While.many.are.
using.it.for.better.operations,.some.of.them.are.noticing.that.it.can.also.be.used.for.
security.by.providing.broader.view.of.vulnerabilities.and.risks..Meanwhile,.deep.
learning.is.coming.up.as.a.key.role.by.providing.predictive.analytics.solutions..Deep.
learning.and.big.data.analytics.are.becoming.two.high-focus.of.data.science..Threat.
intelligence.becoming.more.and.more.effective..Since.it.is.based.on.how.much.data.
collected.about.active.threats,.this.reason.has.taken.many.independent.vendors.into.
partnerships..In.this.chapter,.we.explore.big.data.and.big.data.analytics.with.its.
benefits..And.we.provide.a.brief.overview.of.deep.analytics.and.finally.we.present.
collaborative.threat.Detection..We.also.investigate.some.aspects.of.standards.and.key.
functions.of.it..We.conclude.by.presenting.benefits.and.challenges.of.collaborative.
threat.detection.