Security Issues and Privacy Concerns in Industry 4.0 Applications

Herausgegeben:David, Shibin; Anand, R. S.; Jeyakrishnan, V.

• Gebundenes Buch

Produktbeschreibung

SECURITY ISSUES AND PRIVACY CONCERNS IN INDUSTRY 4.0 APPLICATIONS

Written and edited by a team of international experts, this is the most comprehensive and up-to-date coverage of the security and privacy issues surrounding Industry 4.0 applications, a must-have for any library.

The scope of Security Issues and Privacy Concerns in Industry 4.0 Applications is to envision the need for security in Industry 4.0 applications and the research opportunities for the future. This book discusses the security issues in Industry 4.0 applications for research development. It will also enable the reader to develop solutions for the security threats and attacks that prevail in the industry. The chapters will be framed on par with advancements in the industry in the area of Industry 4.0 with its applications in additive manufacturing, cloud computing, IoT (Internet of Things), and many others. This book helps a researcher and an industrial specialist to reflect on the latest trends and the need for technological change in Industry 4.0.

Smart water management using IoT, cloud security issues with network forensics, regional language recognition for industry 4.0, IoT-based health care management systems, artificial intelligence for fake profile detection, and packet drop detection in agriculture-based IoT are covered in this outstanding new volume. Leading innovations such as smart drone for railway track cleaning, everyday life-supporting blockchain and big data, effective prediction using machine learning, classification of dog breed based on CNN, load balancing using the SPE approach and cyber culture impact on media consumers are also addressed.

Whether a reference for the veteran engineer or an introduction to the technologies covered in the book for the student, this is a must-have for any library.

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Produktdetails

• Verlag: Wiley & Sons / Wiley-Scrivener
• Artikelnr. des Verlages: 1W119775620
• 1. Auflage
• Seitenzahl: 272
• Erscheinungstermin: 24. August 2021
• Englisch
• Abmessung: 238mm x 159mm x 19mm
• Gewicht: 508g
• ISBN-13: 9781119775621
• ISBN-10: 1119775620
• Artikelnr.: 59963896

Autorenporträt

Shibin David is an assistant professor in the Department of Computer Science and Engineering at Karunya Institute of Technology and Sciences, India. His research interest includes cryptography, network security and mobile computing. He has an industry certification from Oracle, several awards, and a number of publications to his credit. R. S. Anand is a researcher in the field of mechanical engineering at the Karunya Institute of Technology and Sciences, India, after being an assistant professor at the Narayana Guru College of Engineering from 2014 to 2016. He has numerous papers and presentations to his credit. V. Jeyakrishnan, PhD, is an assistant professor at Saintgits College of Engineering, Kottayam, India. His research area includes wireless networks, cloud computing and its applications. He has a number of publications in his research area. M. Niranjanamurthy, PhD, is an assistant professor in the Department of Computer Applications, M S Ramaiah Institute of Technology, Bangalore, Karnataka. He received his doctorate in computer science from JJTU, Rajasthan. He has over ten years of teaching experience and two years of industry experience as a software engineer. He has published four books, 70 papers, and has filed for 17 Patents with three so far granted. He is a reviewer for 22 international academic journals and has twice won Best Research Journal Reviewer award. He has numerous other awards and in is active in research associations.

Inhaltsangabe

Preface xiii

1 Industry 4.0: Smart Water Management System Using IoT 1
S. Saravanan, N. Renugadevi, C.M. Naga Sudha and Parul Tripathi

1.1 Introduction 2

1.1.1 Industry 4.0 2

1.1.2 IoT 2

1.1.3 Smart City 3

1.1.4 Smart Water Management 3

1.2 Preliminaries 4

1.2.1 Internet World to Intelligent World 4

1.2.2 Architecture of IoT System 4

1.2.3 Architecture of Smart City 6

1.3 Literature Review on SWMS 7

1.3.1 Water Quality Parameters Related to SWMS 8

1.3.2 SWMS in Agriculture 8

1.3.3 SWMS Using Smart Grids 9

1.3.4 Machine Learning Models in SWMS 10

1.3.5 IoT-Based SWMS 11

1.4 Conclusion 11

References 12

2 Fourth Industrial Revolution Application: Network Forensics Cloud Security Issues 15
Abdullah Ayub Khan, Asif Ali Laghari, Shafique Awan and Awais Khan Jumani

2.1 Introduction 16

2.1.1 Network Forensics 16

2.1.2 The Fourth Industrial Revolution 17

2.1.2.1 Machine-to-Machine (M2M) Communication 18

2.1.3 Cloud Computing 18

2.1.3.1 Infrastructure-as-a-Service (IaaS) 19

2.1.3.2 Challenges of Cloud Security in Fourth Industrial Revolution 19

2.2 Generic Model Architecture 20

2.3 Model Implementation 24

2.3.1 OpenNebula (Hypervisor) Implementation Platform 24

2.3.2 NetworkMiner Analysis Tool 25

2.3.3 Performance Matrix Evaluation & Result Discussion 27

2.4 Cloud Security Impact on M2M Communication 28

2.4.1 Cloud Computing Security Application in the Fourth Industrial Revolution (4.0) 29

2.5 Conclusion 30

References 31

3 Regional Language Recognition System for Industry 4.0 35
Bharathi V, N. Renugadevi, J. Padmapriya and M. Vijayprakash

3.1 Introduction 36

3.2 Automatic Speech Recognition System 39

3.2.1 Preprocessing 41

3.2.2 Feature Extraction 42

3.2.2.1 Linear Predictive Coding (LPC) 42

3.2.2.2 Linear Predictive Cepstral Coefficient (LPCC) 44

3.2.2.3 Perceptual Linear Predictive (PLP) 44

3.2.2.4 Power Spectral Analysis 44

3.2.2.5 Mel Frequency Cepstral Coefficients 45

3.2.2.6 Wavelet Transform 46

3.2.3 Implementation of Deep Learning Technique 46

3.2.3.1 Recurrent Neural Network 47

3.2.3.2 Long Short-Term Memory Network 47

3.2.3.3 Hidden Markov Models (HMM) 47

3.2.3.4 Hidden Markov Models - Long Short-Term Memory Network (HMM-LSTM) 48

3.2.3.5 Evaluation Metrics 49

3.3 Literature Survey on Existing TSRS 49

3.4 Conclusion 52

References 52

4 Approximation Algorithm and Linear Congruence: An Approach for Optimizing the Security of IoT-Based Healthcare Management System 55
Anirban Bhowmik and Sunil Karforma

4.1 Introduction 56

4.1.1 IoT in Medical Devices 56

4.1.2 Importance of Security and Privacy Protection in IoT-Based Healthcare System 57

4.1.3 Cryptography and Secret Keys 58

4.1.4 RSA 58

4.1.5 Approximation Algorithm and Subset Sum Problem 58

4.1.6 Significance of Use of Subset Sum Problem in Our Scheme 59

4.1.7 Linear Congruence 60

4.1.8 Linear and Non-Linear Functions 61

4.1.9 Pell's Equation 61

4.2 Literature Survey 62

4.3 Problem Domain 63

4.4 Solution Domain and Objectives 64

4.5 Proposed Work 65

4.5.1 Methodology 65

4.5.2 Session Key Generation 65

4.5.3 Intermediate Key Generation 67