Predictive Data Security using AI: Insights and Issues of Blockchain, IoT, and DevOps

Preface
Acknowledgements
Contents
About the Editors
A Comprehensive Study of Security Aspects in Blockchain
	1 Introduction
	2 Characteristics of Blockchain Technology
	3 Working of Blockchain
	4 Analysis of Security in Blockchain
		4.1 Risks to Blockchain
		4.2 Attacks on Blockchain
	5 Security Enhancements
	6 Applications of Blockchain
	7 Trade-Offs and Challenges of Blockchain Technology
	8 Conclusion
	References
An Exploration Analysis of Social Media Security
	1 Introduction to Social Media Security and Its Evolution
	2 Important Issues Involving Security for Social Media
		2.1 Privacy of Data
		2.2 Data Mining
		2.3 Virus and Malware Attacks
		2.4 Legal Issues
	3 Risks and Challenges of Social Media Security
		3.1 Information Revelation
		3.2 Location Spillage
		3.3 Cyberbullying and Cyberstalking
		3.4 Cyber Terrorism
		3.5 Reputation Misfortune
		3.6 Identity Theft
	4 Social Media Networks Security Solutions
		4.1 Watermarking
		4.2 Steganalysis
		4.3 Digital Oblivion
		4.4 Storage Encryption
		4.5 Detection of Malware and Phishing
		4.6 Prediction of Cyberattacks Through Monitoring Social Media
		4.7 Time Lag-Based Modelling for Software Vulnerability Exploitation Process
		4.8 Session Hijacking Counter Measures
		4.9 Privacy Set-Up on Social Networking Sites
	5 Conclusion
	References
A Pragmatic Analysis of Security Concerns in Cloud, Fog, and Edge Environment
	1 Introduction to Cloud Computing
	2 Introduction to Fog Computing
	3 Introduction to Edge Computing
	4 Security Threats of Cloud Fog and Edge Computing
	5 Potential Solution of Cloud Fog and Edge Computing
	6 Conclusion and Future Scope
	References
Secure Information and Data Centres: An Exploratory Study
	1 Introduction
		1.1 History of Data Centre
		1.2 Importance of Data Centres in a Business Environment
	2 Core Parts of a Data Centre
		2.1 Network Infrastructure
		2.2 Storage Infrastructure
		2.3 Server Infrastructure
		2.4 Computing Resources
		2.5 Categories of Data Centre Facilities
	3 Requirements of a Modern Data Centre
		3.1 Abundant, Reliable Power
		3.2 Cool Conditions
		3.3 Physical and Virtual Security Measures
	4 Tiered Data Centres
		4.1 Uptime Institute
	5 Challenges in Data centre Networking
		5.1 Data Security
		5.2 Power Management
		5.3 Capacity Planning
		5.4 The Internet of Things (IoT)
		5.5 Mobile Enterprise
		5.6 Real-Time Reporting
		5.7 Balancing Cost Controls with Efficiency
	6 Threats Faced by Data Centres in India
		6.1 Inadequate Cognizance of Assets
		6.2 Disproportionate Energy Exhaustion
		6.3 Inefficient Capacity Planning
		6.4 Unfortunate Staff Productivity
		6.5 Long Recovery Periods
		6.6 Growing Security Concerns
	7 Security Threats of Data Centre
		7.1 Classes of Data Centre Security
		7.2 Who Needs Data Centre Security?
	8 Cybersecurity Threats to Heed
		8.1 Phishing Engineering Attacks
		8.2 Ransomware
		8.3 Cyberattacks Against Hosted Services
		8.4 IoT-Based Attacks
		8.5 Internal Attacks
		8.6 Unpatched Security Susceptibility and Bugs
	9 How to Keep Data Centre Secure
	10 How to Curb These Attacks
		10.1 Secure Your Hardware
		10.2 Encrypt and Backup Data
		10.3 Create a Security-Focused Workplace Culture
		10.4 Invest in Cybersecurity Insurance
		10.5 Physical Security
		10.6 Virtual Security
	11 How to Secure Data Centres Against or After Cyberattacks
		11.1 Securing Different Regions Through Network Segmentation
		11.2 Moving Beyond Segmentation to Cyber
		11.3 Advanced Attacks and Mature Attacks
		11.4 Behavioural
		11.5 Preempt the Silos
	12 Checklist to Help with Security Arrangements
	13 Benefits of Cybersecurity
	14 Conclusion
	References
Blockchain-Based Secure E-voting System Using Aadhaar Authentication
	1 Introduction
	2 Related Work
	3 Proposed Work
		3.1 System Architecture
	4 Implementation Details
	5 Security Analysis of Proposed System
	6 Comparison with Existing Techniques
	7 Conclusion and Future Scope
	References
DevOps Tools: Silver Bullet for Software Industry
	1 Introduction
		1.1 Background
	2 DevOps Life Cycle
		2.1 Continuous Development
		2.2 Continuous Integration
		2.3 Continuous Testing
		2.4 Continuous Deployment
		2.5 Continuous Monitoring
		2.6 Continuous Feedback
		2.7 Continuous Operations
	3 DevOps Tools
		3.1 Code
		3.2 Build
		3.3 Test
		3.4 Delivery
		3.5 Deployment
		3.6 Monitor
	4 DevOps in Industry and Education
	5 Conclusion and Future Perspective
	References
Robust and Secured Reversible Data Hiding Approach for Medical Image Transmission over Smart Healthcare Environment
	1 Introduction
	2 Related Work
	3 Proposed Work
		3.1 Watermark Embedding and Extraction
		3.2 Watermark Encryption and Decryption
	4 Experimental Results and Discussion
		4.1 Imperceptibility Test
		4.2 Robustness Test
		4.3 Security Test
		4.4 Computational Cost
	5 Conclusions
	References
Advancements in Reversible Data Hiding Techniques and Its Applications in Healthcare Sector
	1 Introduction
	2 Methods of Secure Communication
		2.1 Steganography
		2.2 Reversible Data Hiding (RDH)
		2.3 Digital Watermarking
	3 Related Work
		3.1 Efficiency Parameters
		3.2 Related Works on Reversible Data Hiding
		3.3 Related Works on Reversible Watermarking
	4 Medical Image Datasets for the Research Work
	5 Research Challenges
	6 Conclusion
	References
Security Issues in Deep Learning
	1 Introduction
		1.1 Implementations of Deep Learning
	2 Background
		2.1 Deep Learning
		2.2 Deep Neural Networks (DNNs)
		2.3 Artificial Intelligence
		2.4 DNNs Properties
		2.5 Strategies for Secrecy for In-Depth Learning
	3 In-Depth Reading of Private Data Frames
		3.1 Shokri and Shmatikov
		3.2 SecureML
		3.3 Google
		3.4 CryptoNets
		3.5 MiniONN
		3.6 Chameleon
		3.7 DeepSecure
	4 Deep Learning Attack
		4.1 Trained Model
		4.2 Inputs and Prediction Results
	5 Attack that Destroys Example
		5.1 Introduction of Model Extraction Attack
		5.2 Adversary Model
		5.3 Alternative Released Information
	6 Possible Attacks of Example
		6.1 Introducing the Model Inversion Attack
		6.2 Suspected Membership Attack
	7 Poison Attack
		7.1 Attack Assaults on Ordinary Supervised Analysis (LR)
		7.2 Poisoning Assaults in Conventional Unsupervised Learning
		7.3 Poison Attack on Deep Learning
		7.4 Poison Assault on Strengthening Training
	8 Adversarial Attack
		8.1 How to Attack Enemies
	9 Unlock Problems
	10 Conclusion
	References
CNN-Based Models for Image Forgery Detection
	1 Introduction
	2 Theoretical Background
	3 Dataset Description
	4 Methodology
		4.1 Data Pre-processing
		4.2 Training Models
		4.3 Workflow of the Proposed CNN Model
	5 Result and Analysis
		5.1 Hyper-parameters
		5.2 Pseudocode
		5.3 Evaluation Metrics
		5.4 Training and Validation Loss Curve
		5.5 Confusion Matrix
	6 Conclusion and Future Scope
	References
Malicious URL Detection Using Machine Learning
	1 Introduction
	2 Related Work
	3 Overview of Principles of Detecting Malicious URLs
		3.1 Blacklisting or Heuristic Approaches
		3.2 Machine Learning Approaches
	4 Datasets
	5 Feature Extraction
		5.1 URL-Based Lexical Features
		5.2 DNS-Based Features
		5.3 Webpage Content-Based Features
	6 Machine Learning Algorithms for Malicious URL Detection
	7 Practical Issues and Open Problems
	8 Conclusion
	References