Securing IoT and Big Data: Next Generation Intelligence

191 Pages·2021·4.415 MB·English

by  Vijayalakshmi Saravanan, Alagan Anpalagan, T. Poongodi, Firoz Khan

Securing IoT and Big Data
Internet of Everything (IoE): Security and Privacy Paradigm
Series Editors: Vijender Kumar Solanki, Raghvendra Kumar, and Le Hoang Son
Blockchain Technology
Fundamentals, Applications, and Case Studies
Edited by E Golden Julie, J. Jesu Vedha Nayahi, and Noor Zaman Jhanjhi
Data Security in Internet of Things Based RFID and WSN Systems
Applications
Edited by Rohit Sharma, Rajendra Prasad Mahapatra, and Korhan Cengiz
Securing IoT and Big Data
Next Generation Intelligence
Edited by Vijayalakshmi Saravanan, Anpalagan Alagan, T. Poongodi, and Firoz
Khan
Distributed Artificial Intelligence
A Modern Approach
Edited by Satya Prakash Yadav, Dharmendra Prasad Mahato, and Nguyen Thi Dieu
Linh
Security and Trust Issues in Internet of Things
Blockchain to the Rescue
Edited by Sudhir Kumar Sharma, Bharat Bhushan, and Bhuvan Unhelkar
Internet of Medical Things
Paradigm of Wearable Devices
Edited by Manuel N. Cardona, Vijender Kumar Solanki, and Cecilia García Cena
Integration of WSNs into Internet of Things
A Security Perspective
Edited by Sudhir Kumar Sharma, Bharat Bhushan, Raghvendra Kumar, Aditya
Khamparia, and Narayan C. Debnath
For more information about this series, please visit: https://www.crcpress.com/
Internet-of-Everything-IoE-Security-and-Privacy-Paradigm/book-series/CRCIOESPP
Securing IoT and
Big Data
Next Generation Intelligence
Edited by
Vijayalakshmi Saravanan, Alagan Anpalagan,
T. Poongodi, and Firoz Khan
First edition published 2021
by CRC Press
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Library of Congress Cataloging-in-Publication Data
Names: Saravanan, Vijayalakshmi, editor. | Anpalagan, Alagan, editor. |
Poongodi, T., editor. | Khan, Firoz, editor.
Title: Securing IoT and big data : next generation intelligence / edited by
Vijayalakshmi Saravanan, Alagan Anpalagan, T. Poongodi, Firoz Khan.
Description: First edition. | Boca Raton : CRC Press, 2021. | Includes
bibliographical references and index.
Identifiers: LCCN 2020028013 (print) | LCCN 2020028014 (ebook) | ISBN
9780367432881 (hardback) | ISBN 9781003009092 (ebook)
Subjects: LCSH: Internet of things. | Big data. | Internet of
things--Security measures. | Big data--Security measures.
Classification: LCC TK5105.8857 .S385 2021 (print) | LCC TK5105.8857
(ebook) | DDC 004.67/8--dc23
LC record available at https://lccn.loc.gov/2020028013
LC ebook record available at https://lccn.loc.gov/2020028014
ISBN: 978-0-367-43288-1 (hbk)
ISBN: 978-1-003-00909-2 (ebk)
Typeset in Times
by SPi Global, India
Contents
Preface .......................................................................................................................xi
Acknowledgements .................................................................................................xiii
Editors ......................................................................................................................xv
Contributors ...........................................................................................................xvii
Chapter 1 Foundation of Big Data and Internet of Things:
Applications and Case Study ..............................................................1
1.1 Introduction to Big Data and Internet of Things.......................1
1.1.1 Big Data Management Systems in Healthcare .............3
1.1.2 Challenges in Healthcare ..............................................5
1.1.3 Sequencing Genomic Data ...........................................6
1.1.4 Deep Learning Applied to Genomic Data ....................8
1.1.5 Genomic Data and Modern Healthcare ......................10
1.2 Background and Rise of Internet of Things ............................11
1.2.1 IoT in Real-Time Healthcare Applications.................12
1.2.1.1 Wearable Front-End Device ........................12
1.2.1.2 Smartphone Application ..............................12
1.2.1.3 Cloud and Algorithms .................................12
1.2.1.4 How Does It Work in Real-Time? ...............12
1.3 Summary .................................................................................12
References .........................................................................................13
Chapter 2 Securing IoT with Blockchain: Challenges, Applications,
and Techniques .................................................................................15
2.1 Introduction .............................................................................15
2.2 Security Issues of IoT .............................................................17
2.2.1 IoT Malware ...............................................................17
2.2.2 Device Updates Management ....................................17
2.2.3 Manufacturing Defects ...............................................18
2.2.4 Security of Massively Generated Data .......................18
2.2.5 Authorization and Authentication Issues ...................18
2.2.6 Botnet Attacks ............................................................19
2.3 Introduction to Blockchain .....................................................19
2.3.1 Public Blockchain ......................................................20
2.3.2 Private Blockchain .....................................................20
2.3.3 Consortium Blockchain .............................................20
2.4 Blockchain and IoT Integration: An Overview .......................21
v
vi Contents
2.5 Applications of Integration .....................................................22
2.5.1 Smart Homes and Cities .............................................22
2.5.2 Healthcare ..................................................................22
2.5.3 Internet of Vehicles ....................................................23
2.5.4 Smart Manufacturing .................................................23
2.5.5 Supply Chain ..............................................................23
2.5.6 Smart Energy Grids ....................................................24
2.6 Existing Research on Blockchain-Based IoT Security ...........24
2.6.1 Lightweight IoT Nodes as Thin Clients .....................26
2.6.2 IoT Gateways as Blockchain Nodes ..........................28
2.6.3 IoT Nodes Integrated with Blockchain Clients ..........31
2.6.4 IoT Nodes as Regular Sensors ...................................32
2.7 Conclusion and Future Work ..................................................35
References .........................................................................................35
Chapter 3 IoT and Big Data Using Intelligence ................................................39
3.1 IoT in a Nutshell .....................................................................39
3.2 The Buzzword: Big Data in a Nutshell ...................................41
3.3 IoT vs Big Data .......................................................................44
3.4 Data Generation – Machine vs Human ...................................45
3.4.1 Machine-Generated Data ...........................................45
3.4.2 Human-Generated Data .............................................46
3.5 Data Stream, Management, and Progression
Using IoT and Big Data Approach .........................................47
3.5.1 Data Streaming in IoT ................................................48
3.6 IoT and Big Data Working Together Using Intelligence ........51
3.7 Working Challenges ................................................................53
3.7.1 Component Convergence Challenges (CCC) .............54
3.7.2 Embedded Network Challenges (ENC) .....................55
3.7.3 Analytics and Application Challenges (AAC) ...........55
3.7.4 Ethical and Security Challenges (ESC) .....................55
3.7.5 IoT Adoption Challenges (IAC) .................................56
3.8 Conclusion ..............................................................................58
References .........................................................................................58
Chapter 4 Compulsion for Cyber Intelligence for Rail Analytics
in IoRNT ...........................................................................................59
4.1 Introduction .............................................................................59
4.2 Computer-Based Intelligence .................................................60
4.2.1 Cyber Threat Intelligence...........................................61
4.2.2 Big Data and Analytics ..............................................62
4.3 Analytics Types: Descriptive, Prescriptive, and Predictive ....63
4.4 Understanding Predictive and Concise Analysis ....................64
Contents vii
4.4.1 Analytical Methods ....................................................64
4.4.2 Descriptive Analytics .................................................64
4.4.3 Predictive Analytics ...................................................65
4.4.4 Prescriptive Analytics ................................................66
4.5 Railway Networks ...................................................................67
4.5.1 Industry Pan Rail Directions ......................................68
4.5.1.1 Marketplace Size ........................................68
4.5.1.2 Investment/Evolution ..................................68
4.5.1.3 Government Initiatives ...............................69
4.5.1.4 Road Ahead ................................................69
4.6 Rail Analytics ..........................................................................70
4.7 Internet of Rail Network Things .............................................71
4.7.1 From Application Enabling Interface to IoT ..............72
4.7.2 Investing in Intelligence .............................................72
4.8 Big Data in Rail Intelligence Based on Cyber Threat ............75
4.8.1 An Effective Cyber Security Strategy
for the Rail Sector.......................................................76
4.8.1.1 Dedicated Skills ..........................................76
4.9 Cyber Security Risk Management Strategic
and Tactical Capabilities .........................................................78
4.10 Cyber-Attacks Affecting Railways .........................................78
4.11 Railway Cyber Security: Railway Operations and Assets
Security ...................................................................................80
4.11.1 Cyber Security Railway Future Vulnerabilities .........80
4.11.2 Cyber Security in the Fight Against Railways ...........81
4.12 Conclusion ..............................................................................82
References .........................................................................................82
Chapter 5 Big Data and IoT Forensics ..............................................................85
5.1 Background and Introduction .................................................85
5.2 Types of IoT Forensics............................................................86
5.2.1 Cloud Forensics .........................................................87
5.2.2 Network Forensics .....................................................88
5.2.3 Device-Level Forensics ..............................................88
5.3 Sources and Nature of Data ....................................................89
5.3.1 Big Data .....................................................................90
5.3.2 IoT Forensics Data .....................................................91
5.4 Role of Big Data in IoT Forensics ..........................................93
5.4.1 Big Data Technologies ...............................................93
5.4.1.1 Hadoop .......................................................93
5.4.1.2 Spark ...........................................................93
5.4.1.3 Kafka ..........................................................94
5.4.2 Big Data Analytics .....................................................94
viii Contents
5.4.2.1 Data Stream Learning .................................95
5.4.2.2 Deep Learning ............................................95
5.4.2.3 Incremental and Ensemble Learning ..........96
5.4.2.4 Granular Computing-Based Machine
Learning......................................................96
5.5 IoT Forensics Investigation Framework .................................97
5.5.1 Steps for IoT Forensics Investigation.........................97
5.5.1.1 Evidence Collection ...................................97
5.5.1.2 Examination ...............................................97
5.5.1.3 Analysis ......................................................97
5.5.1.4 Reporting ....................................................98
5.5.2 Forensic Soundness ....................................................98
5.5.2.1 Meaning ......................................................98
5.5.2.2 Errors ..........................................................98
5.5.2.3 Transparency and Trustworthiness .............98
5.5.2.4 Experience ..................................................98
5.6 Challenges in IoT Forensics ...................................................99
5.6.1 Variety of Data ...........................................................99
5.6.2 Security ......................................................................99
5.6.3 Privacy ........................................................................99
5.6.4 Data Organization ....................................................100
5.7 Case Studies Using IoT Forensics ........................................100
5.7.1 Smart Health Monitoring System ............................100
5.7.2 Amazon Echo as a Use Case ....................................101
5.7.3 IoT in a Smart Home ................................................101
5.8 Solution Methodology Proposed ..........................................101
5.8.1 Machine Learning Algorithms .................................101
5.8.2 Public Digital Ledger ...............................................102
5.9 Opportunities and Future Technologies ................................102
5.9.1 Forensic Data Dependability ....................................102
5.9.2 Models and Tools .....................................................102
5.9.3 Smart Analysis and Presentation ..............................102
5.9.4 Resolving Legal Challenges.....................................102
5.9.5 Smart Forensics for IoT ...........................................103
5.9.6 Emerging Technologies for IoT ...............................103
5.10 Conclusion ............................................................................103
References .......................................................................................104
Chapter 6 Integration of IoT and Big Data in the Field of Entertainment
for Recommendation System ..........................................................109
6.1 Introduction ...........................................................................109
6.2 Background ...........................................................................110
6.3 Analysis and Algorithms .......................................................111
Contents ix
6.4 Case Study ............................................................................118
6.5 Discussion .............................................................................119
6.6 Conclusion ............................................................................120
References .......................................................................................120
Chapter 7 Secure and Privacy Preserving Data Mining
and Aggregation in IoT Applications ..............................................123
7.1 Introduction ...........................................................................123
7.2 Privacy and Security Challenges in IoT Applications ..........124
7.2.1 Identification ............................................................124
7.2.2 Localizing and Tracking ..........................................124
7.2.3 Life Cycle Transitions ..............................................124
7.2.4 Secure Data Transmission ........................................125
7.3 Secure and Privacy Preserving Data Mining Techniques .....125
7.3.1 Privacy Preserving Techniques at Data
Collection Layer .......................................................126
7.3.1.1 Additive Noise ..........................................126
7.3.1.2 Multiplicative Noise .................................126
7.3.2 Privacy Preserving at Data Publishing Layer ...........127
7.3.2.1 Generalization ..........................................127
7.3.2.2 Suppression ..............................................127
7.3.2.3 Anatomization ..........................................127
7.3.2.4 K-Anonymity ............................................127
7.3.2.5 L-Diversity ...............................................128
7.3.2.6 Personalized Privacy .................................128
7.3.2.7 Differential Privacy ..................................128
7.3.2.8 ∈-Differential Privacy ..............................129
7.3.3 Privacy Preserving at Data Mining Output Layer ....129
7.3.3.1 Association Rule Hiding ..........................130
7.3.3.2 Classifier Effectiveness Downgrading ......130
7.3.3.3 Query Auditing and Inference Control .....130
7.3.4 Distributed Privacy ...................................................130
7.3.4.1 One out of Two Oblivious Transfer ..........130
7.3.4.2 Homomorphic Encryption ........................131
7.4 Security Ensuring Techniques for Privacy
Preserving Data Aggregation ................................................131
7.4.1 Privacy Preservation Using Homomorphic
Encryption and Advanced Encryption
Standard (AES) ........................................................133
7.4.1.1 Implementation of Homomorphic
Encryption and AES Algorithm ................133
7.4.1.2 Encryption and Exchange .........................133
7.4.1.3 Decryption and Confusion........................134