Anomaly Detection: Techniques and Applications

190 Pages·2021·8.828 MB·English

by  Saira Banu, Shriram Raghunathan, Dinesh Mavaluru, A. Syed Mustafa

COMPUTER SCIENCE, TECHNOLOGY AND APPLICATIONS

A D
NOMALY ETECTION

TECHNIQUES AND APPLICATIONS

No part of this digital document may be reproduced, stored in a retrieval system or transmitted in any form or
by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no
expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No
liability is assumed for incidental or consequential damages in connection with or arising out of information
contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in
rendering legal, medical or any other professional services.
COMPUTER SCIENCE, TECHNOLOGY
AND APPLICATIONS

Additional books and e-books in this series can be found on Nova’s
website under the Series tab.
COMPUTER SCIENCE, TECHNOLOGY AND APPLICATIONS

A D
NOMALY ETECTION

TECHNIQUES AND APPLICATIONS

SAIRA BANU
SHRIRAM RAGHUNATHAN
DINESH MAVALURU
AND
A. SYED MUSTAFA
EDITORS
Copyright © 2021 by Nova Science Publishers, Inc.

All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted
in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying,
recording or otherwise without the written permission of the Publisher.

We have partnered with Copyright Clearance Center to make it easy for you to obtain permissions to
reuse content from this publication. Simply navigate to this publication’s page on Nova’s website and
locate the “Get Permission” button below the title description. This button is linked directly to the
title’s permission page on copyright.com. Alternatively, you can visit copyright.com and search by
title, ISBN, or ISSN.

For further questions about using the service on copyright.com, please contact:
Copyright Clearance Center
Phone: [phone] Fax: [phone] E-mail: [email protected].

NOTICE TO THE READER
The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or
implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is
assumed for incidental or consequential damages in connection with or arising out of information
contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary
damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any
parts of this book based on government reports are so indicated and copyright is claimed for those parts
to the extent applicable to compilations of such works.

Independent verification should be sought for any data, advice or recommendations contained in this
book. In addition, no responsibility is assumed by the Publisher for any injury and/or damage to
persons or property arising from any methods, products, instructions, ideas or otherwise contained in
this publication.

This publication is designed to provide accurate and authoritative information with regard to the subject
matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in
rendering legal or any other professional services. If legal or any other expert assistance is required, the
services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS
JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A
COMMITTEE OF PUBLISHERS.

Additional color graphics may be available in the e-book version of this book.

Library of Congress Cataloging-in-Publication Data

ISBN: (cid:28)(cid:26)(cid:27)(cid:16)(cid:20)(cid:16)(cid:24)(cid:22)(cid:25)(cid:20)(cid:28)(cid:16)(cid:22)(cid:24)(cid:24)(cid:16)(cid:27)(cid:3)(cid:11)(cid:72)(cid:37)(cid:82)(cid:82)(cid:78)(cid:12)

Published by Nova Science Publishers, Inc. † New York
CONTENTS

Preface vii
Acknowledgment ix
Chapter 1 Secured and Automated Key Establishment
and Data Forwarding Scheme for the Internet
of Things 1
N. V. Kousik, R. Arshath Raja, N. Yuvaraj
and S. Anbu Chelian
Chapter 2 A Study of Enhanced Anomaly Detection
Techniques Using Evolutionary-Based
Optimization for Improved Detection Accuracy 19
Vidhya Sathish and Sheik Abdul Khader
Chapter 3 Anomaly Detection and Applications 47
Huichen Shu
Chapter 4 An Evolutionary Study on SIoT
(Social Internet of Things) 77
Dinesh Mavaluru and Jayabrabu Ramakrishnan
vi Contents
Chapter 5 A Critical Study on Advanced Machine Learning
Classification of Human Emotional State
Recognition Using Facial Expressions 93
Jayabrabu Ramakrishnan and Dinesh Mavaluru
Chapter 6 Anomaly Detection for Data Aggregation in
Wireless Sensor Networks 139
Beski Prabaharan and Saira Banu
Chapter 7 Algorithm for Real Time Anomalous
User Detection from Call Detail Record 151
Saira Banu and Beski Prabaharan
Chapter 8 Secured Transactions from the Anomaly User
Using 2 Way SSL 159
Syed Mustafa and Mr. Madhivanan
About the Editors 171
Index 173
PREFACE

Chapter 1 - This chapter presents the scheme for ensuring the security
of data through the IoT sensors. LC-KES collaborative key management
technique is used for guaranteeing the security of data transmitted to the
servers. This chapter proposes the SAKE-MBAT-FNN and Modified BAT
algorithm for the cryptographic action. The proposed algorithm increases
the performance in terms of throughput and network life time.
Chapter 2 - This chapter discusses the anomaly based Intrusion
Detection systems. The study related to utilization of evolutionary based
hybrid approaches are presented and its successive rate in accurate
extraction of ‘malicious’ patterns from existence when compared to other
approaches are proven. This chapter also discusses the challenging
research requirement which need to be fulfilled in the cyber research
community.
Chapter 3 - This chapter introduces the structure of outlier detection
algorithm. It also presents the techniques for detecting the outlier using the
tools like python and Rapid miner. Proximity based, PCA, local outlier
detection and high dimensional outlier detection techniques are explained
in detail.
Chapter 4 - This chapter discusses the issues with respect to vulnerable
data in IoT devices. It presents the CLA technique for detecting the
viii Saira Banu, Shriram Raghunathan, Dinesh Mavaluru et al.
vulnerable data and also highlights the challenges involved in handling
those data.
Chapter 5 - This chapter determines the fundamentals for Facial
Expression Recognition (FER) techniques. The various classifiers used for
examining the facial expression recognition system are discussed and the
results are compared. The best suited classifier for FER is identified.
Chapter 6: This chapter uses aggregation schemes for securing the
data from anomaly users in the wireless sensor networks. This technique is
used for both homogeneous and heterogeneous WSN.
Chapter 7 - This chapter discusses the methodology to find the
anomalous users in telecommunication. The spam callers are detected
using the information in the call detail record.
Chapter 8 - This chapter addresses the major challenge of securing the
transactions from the anomaly user using the SSL and micro services. In
this chapter. 2-way SSL is used for protecting the data using spring boot
technology.