Security Issues and Privacy Concerns in Industry 4.0 Applications

Preface
1 Industry 4.0: Smart Water Management System Using IoT
S. Saravanan, N. Renugadevi, C.M. Naga Sudha and Parul Tripathi
1.1 Introduction
1.1.1 Industry 4.0
1.1.2 IoT
1.1.3 Smart City
1.1.4 Smart Water Management
1.2 Preliminaries
1.2.1 Internet World to Intelligent World
1.2.2 Architecture of IoT System
1.2.3 Architecture of Smart City
1.3 Literature Review on SWMS
1.3.1 Water Quality Parameters Related to SWMS
1.3.2 SWMS in Agriculture
1.3.3 SWMS Using Smart Grids
1.3.4 Machine Learning Models in SWMS
1.3.5 IoT-Based SWMS
1.4 Conclusion
References
2 Fourth Industrial Revolution Application: Network Forensics
Cloud Security Issues
Abdullah Ayub Khan, Asif Ali Laghari, Shafque Awan and Awais Khan Jumani
2.1 Introduction
2.1.1 Network Forensics
2.1.2 Te Fourth Industrial Revolution 17vi Contents
2.1.2.1 Machine-to-Machine (M2M)
Communication
2.1.3 Cloud Computing
2.1.3.1 Infrastructure-as-a-Service (IaaS)
2.1.3.2 Challenges of Cloud Security in Fourth Industrial Revolution
2.2 Generic Model Architecture
2.3 Model Implementation
2.3.1 OpenNebula (Hypervisor) Implementation Platform
2.3.2 NetworkMiner Analysis Tool
2.3.3 Performance Matrix Evaluation & Result Discussion
2.4 Cloud Security Impact on M2M Communication
2.4.1 Cloud Computing Security Application in the Fourth Industrial Revolution (4.0)
2.5 Conclusion
References
3 Regional Language Recognition System for Industry 4.0
Bharathi V, N. Renugadevi, J. Padmapriya and M. Vijayprakash
3.1 Introduction
3.2 Automatic Speech Recognition System
3.2.1 Preprocessing
3.2.2 Feature Extraction
3.2.2.1 Linear Predictive Coding (LPC)
3.2.2.2 Linear Predictive Cepstral
Coefcient (LPCC)
3.2.2.3 Perceptual Linear Predictive (PLP)
3.2.2.4 Power Spectral Analysis
3.2.2.5 Mel Frequency Cepstral Coefcients
3.2.2.6 Wavelet Transform
3.2.3 Implementation of Deep Learning Technique
3.2.3.1 Recurrent Neural Network
3.2.3.2 Long Short-Term Memory Network
3.2.3.3 Hidden Markov Models (HMM)
3.2.3.4 Hidden Markov Models - Long Short-Term Memory Network (HMM-LSTM)
3.2.3.5 Evaluation Metrics
3.3 Literature Survey on Existing TSRS
3.4 Conclusion
References
4 Approximation Algorithm and Linear Congruence: An Approach for Optimizing the Security of IoT-Based Healthcare Management System
Anirban Bhowmik and Sunil Karforma
4.1 Introduction
4.1.1 IoT in Medical Devices
4.1.2 Importance of Security and Privacy Protection in IoT-Based Healthcare System
4.1.3 Cryptography and Secret Keys
4.1.4 RSA
4.1.5 Approximation Algorithm and Subset Sum Problem
4.1.6 Signifcance of Use of Subset Sum Problem in Our Scheme
4.1.7 Linear Congruence
4.1.8 Linear and Non-Linear Functions
4.1.9 Pell’s Equation
4.2 Literature Survey
4.3 Problem Domain
4.4 Solution Domain and Objectives
4.5 Proposed Work
4.5.1 Methodology
4.5.2 Session Key Generation
4.5.3 Intermediate Key Generation
4.5.4 Encryption Process
4.5.5 Generation of Authentication Code and Transmission File
4.5.6 Decryption Phase
4.6 Results and Discussion
4.6.1 Statistical Analysis
4.6.2 Randomness Analysis of Key
4.6.3 Key Sensitivity Analysis
4.6.4 Security Analysis
4.6.4.1 Key Space Analysis
4.6.4.2 Brute-Force Attack
4.6.4.3 Dictionary Attack
4.6.4.4 Impersonation Attack
4.6.4.5 Replay Attack
4.6.4.6 Tampering Attack
4.6.5 Comparative Analysis
4.6.5.1 Comparative Analysis Related to IoT Attacks
4.6.6 Signifcance of Authentication in Our Proposed Scheme
4.7 Conclusion
References
5 A Hybrid Method for Fake Profle Detection in Social Network Using Artifcial Intelligence
Ajesh F, Aswathy S U, Felix M Philip and Jeyakrishnan V
5.1 Introduction
5.2 Literature Survey
5.3 Methodology
5.3.1 Datasets
5.3.2 Detection of Fake Account
5.3.3 Suggested Framework
5.3.3.1 Pre-Processing
5.3.3.2 Principal Component Analysis (PCA)
5.3.3.3 Learning Algorithms
5.3.3.4 Feature or Attribute Selection
5.4 Result Analysis
5.4.1 Cross-Validation
5.4.2 Analysis of Metrics
5.4.3 Performance Evaluation of Proposed Model
5.4.4 Performance Analysis of Classifers
5.5 Conclusion
References
6 Packet Drop Detection in Agricultural-Based Internet of Tings Platform
Sebastian Terence and Geethanjali Purushothaman
6.1 Introduction
6.2 Problem Statement and Related Work
6.3 Implementation of Packet Dropping Detection in IoT Platform
6.4 Performance Analysis
6.5 Conclusion
References
7 Smart Drone with Open CV to Clean the Railway Track
Sujaritha M and Sujatha R
7.1 Introduction
7.2 Related Work
7.3 Problem Defnition
7.4 Te Proposed System
7.4.1 Drones with Human Intervention
7.4.2 Drones without Human Intervention
7.4.3 Working Model
7.5 Experimental Results
7.6 Conclusion
References
8 Blockchain and Big Data: Supportive Aid for Daily Life
Awais Khan Jumani, Asif Ali Laghari and Abdullah Ayub Khan
8.1 Introduction
8.1.1 Steps of Blockchain Technology Works
8.1.2 Blockchain Private
8.1.3 Blockchain Security
8.2 Blockchain vs. Bitcoin
8.2.1 Blockchain Applications
8.2.2 Next Level of Blockchain
8.2.3 Blockchain Architecture’s Basic Components
8.2.4 Blockchain Architecture
8.2.5 Blockchain Characteristics
8.3 Blockchain Components
8.3.1 Cryptography
8.3.2 Distributed Ledger
8.3.3 Smart Contracts
8.3.4 Consensus Mechanism
8.3.4.1 Proof of Work (PoW)
8.3.4.2 Proof of Stake (PoS)
8.4 Categories of Blockchain
8.4.1 Public Blockchain
8.4.2 Private Blockchain
8.4.3 Consortium Blockchain
8.4.4 Hybrid Blockchain
8.5 Blockchain Applications
8.5.1 Financial Application
8.5.1.1 Bitcoin
8.5.1.2 Ripple
8.5.2 Non-Financial Applications
8.5.2.1 Ethereum
8.5.2.2 Hyperledger
8.6 Blockchain in Different Sectors
8.7 Blockchain Implementation Challenges
8.8 Revolutionized Challenges in Industries
8.9 Conclusion
References 172x Contents
9 A Novel Framework to Detect Effective Prediction Using Machine Learning
Shenbaga Priya, Revadi, Sebastian Terence and Jude Immaculate
9.1 Introduction
9.2 ML-Based Prediction
9.3 Prediction in Agriculture
9.4 Prediction in Healthcare
9.5 Prediction in Economics
9.6 Prediction in Mammals
9.7 Prediction in Weather
9.8 Discussion
9.9 Proposed Framework
9.9.1 Problem Analysis
9.9.2 Preprocessing
9.9.3 Algorithm Selection
9.9.4 Training the Machine
9.9.5 Model Evaluation and Prediction
9.9.6 Expert Suggestion
9.9.7 Parameter Tuning
9.10 Implementation
9.10.1 Farmers and Sellers
9.10.2 Products
9.10.3 Price Prediction
9.11 Conclusion
References
10 Dog Breed Classifcation Using CNN
Sandra Varghese and Remya S
10.1 Introduction
10.2 Related Work
10.3 Methodology
10.4 Results and Discussions
10.4.1 Training
10.4.2 Testing
10.5 Conclusions
References
11 Methodology for Load Balancing in Multi-Agent System Using SPE Approach
S. Ajitha
11.1 Introduction
11.2 Methodology for Load Balancing 208Contents xi
11.3 Results and Discussion
11.3.1 Proposed Algorithm in JADE Tool
11.3.1.1 Sensitivity Analysis
11.3.2 Proposed Algorithm in NetLogo
11.4 Algorithms Used
11.5 Results and Discussion
11.6 Summary
References
12 Te Impact of Cyber Culture on New Media Consumers
Durmuş KoÇak
12.1 Introduction
12.2 Te Rise of the Term of Cyber Culture
12.2.1 Cyber Culture in the 21st Century
12.2.1.1 Socio-Economic Results of Cyber
Culture
12.2.1.2 Psychological Outcomes of Cyber
Culture
12.2.1.3 Political Outcomes of Cyber Culture
12.3 Te Birth and Outcome of New Media Applications
12.3.1 New Media Environments
12.3.1.1 Social Sharing Networks
12.3.1.2 Network Logs (Blog, Weblog)
12.3.1.3 Computer Games
12.3.1.4 Digital News Sites and Mobile Media
12.3.1.5 Multimedia Media
12.3.1.6 What Affects the New Media Consumers’ Tendencies?
12.4 Result
References
Index