AI and Emerging Technologies: Automated Decision-Making, Digital Forensics, and Ethical Considerations

Cover
Half Title
Title
Copyright
Contents
Preface
About the Editors
List of Contributors
Chapter 1 Evolution of Technologies: A Comprehensive Analysis of AI, Blockchain, and Big Data Analytics
	1.1 Introduction
	1.2 Demystifying Blockchain, Artificial Intelligence, and Big
Data Analytics
		1.2.1 Blockchain Technology
		1.2.2 Artificial Intelligence
		1.2.3 Big Data Technology
	1.3 Benefits of Blockchain Technology, Artificial Intelligence,
and Big Data in the Legal Domain
		1.3.1 Blockchain Technology
		1.3.2 Artificial Intelligence
		1.3.3 Big Data Technology
	1.4 Cons of Blockchain, Artificial Intelligence, and Big Data
Technologies in the Legal Sector
		1.4.1 BC Technology
		1.4.2 AI
		1.4.3 BD Technology
	1.5 Enhancing Legal Procedures with Blockchain, AI, and
Big Data Technology
	1.6 Unlocking Opportunities through Technology Integration
	1.7 Challenges in Converging Blockchain, AI, and Big Data
Technologies
	1.8 Conclusion
	References
Chapter 2 Introduction to Digital Forensics
	2.1 Introduction
	2.2 Traditional Digital Investigation Process
	2.3 Digital Forensics Process
		2.3.1 Process of Digital forensics
	2.4 Artificial Intelligence
		2.4.1 AI Is Revolutionizing Digital Forensics
		2.4.2 Challenges and Opportunities at the Intersection
	2.5 AI Techniques in Digital Forensics
		2.5.1 Pattern Recognition and Machine Learning
		2.5.2 Natural Language Processing in Data Recovery
	2.6 AI’s Role in Digital Forensics in the Future
		2.6.1 Forecasting Developments and Trends
		2.6.2 Ethics-Related Concerns and Implications
	2.7 Challenges in Digital Forensics
	2.8 Conclusion
	References
Chapter 3 AI in Digital Forensics
	3.1 Introduction to Digital Forensics
	3.2 The Phases of a Digital Forensics Investigation
	3.3 AI in Digital Forensics: A Potential Game-Changer
	3.4 Real-World Examples: AI Stepping Up in Digital Forensics
	3.5 Diving into the Details: Using AI in Digital Forensics
	3.6 Challenges Digital Forensic Specialists Face
		3.6.1 AI as a Potential Solution
	3.7 AI-Driven Advancements in Digital Forensics Research
	3.8 AI Challenges in Digital Forensics
	3.9 Challenges and Future Directions in AI-Integrated Digital Forensics
	3.10 Making AI Work for Digital Forensics: Conclusion
	3.11 The Future of AI in Digital Forensics
	References
Chapter 4 Forensic Intelligence: Bridging Science and Technology in the Digital Era
	4.1 Introduction
	4.2 A Background
		4.2.1 Toward Digital Forensics as Science
		4.2.2 AI as Technology
	4.3 Methodology of Forensic between Science and Technology
	4.4 The World of Digital and Forensics
		4.4.1 Data
		4.4.2 Computing Systems
		4.4.3 Social Networks and Social Media
		4.4.4 Individual Behavior
		4.4.5 Complexity and Dimensionality
	4.5 Conclusion: Toward Forensic Intelligence
	Bibliography
Chapter 5 Preventing Online Financial Frauds: Carrying Out Digital Forensic Investigation of Artificial Intelligence
	5.1 Introduction
		5.1.1 Using the Power of Digital Forensics for Combating Online Financial Crimes
		5.1.2 Analyzing the Dynamic Nature of Financial Fraud and Using Cybersecurity and Digital Forensic Tools and Techniques as One of the Proposed Solutions
		5.1.3 Proposed Solution for the Digital Forensic Analysis of Online Financial Fraud
	5.2 Using Artificial Intelligence to Detect, Deter, and Prevent Online Financial Fraud and Analyzing the Emerging Technologies
		5.2.1 AI Model for Fraud Detection
		5.2.2 Case Analysis of Emerging Technologies
	5.3 Ethical Considerations and Privacy-Friendly Digital Forensic Investigation of AI
		5.3.1 Principles on Which the Privacy Law Focuses Upon
		5.3.2 Privacy Issues Regarding the Investigation of Online Financial Fraud
		5.3.3 Making Digital Forensics More Privacy-Friendly for AI with Respect to Online Financial Fraud
		5.3.4 Recommendations
	5.4 Conclusion
	References
Chapter 6 Path to Intellectual Revolution in Digital Forensics
	6.1 Introduction
		6.1.1 The Significance of Digital Forensics
		6.1.2 Automated Log Analysis
		6.1.3 Generalized Computation
		6.1.4 Deep Learning
		6.1.5 Log Anomaly Detection
	6.2 Malware Detection
	6.3 Image and Video Analysis
	6.4 Natural Language Processing
		6.4.1 NLP Applications
	6.5 Network Traffic Analysis
		6.5.1 Importance of Network Traffic Analysis
		6.5.2 Network Traffic Analysis Features
	6.6 Forensic Triage
		6.6.1 Tools for Forensics Triage
		6.6.2 Ten Best Digital Forensic Software
		6.6.3 Benefits of Digital Classification
		6.6.4 Prioritizing Devices
		6.6.5 Effective Use of Resources
		6.6.6 Save Time and Reduce Risk
	6.7 Conclusion
	6.8 The Future of Artificial Intelligence in Digital Forensics
		6.8.1 Anticipating Traits and Tendencies
		6.8.2 Ethical Issues and Implications
		Acknowledgments
	References
Chapter 7 AI-Based Environmental Information System for Decision-Making in Public Administrations
	7.1 Introduction
	7.2 State of the Art
	7.3 Knowledge Representation Model
	7.4 Knowledge Evaluation and Integration Method
	7.5 Case Study
		7.5.1 Obtaining Domain Knowledge
		7.5.2 Modeling Views
		7.5.3 Evaluation of the Views
		7.5.4 Relational Support for Each Viewpoint
		7.5.5 Overall Knowledge Assessment Process
		7.5.6 Analysis of the Results
	7.6 Discussion
	7.7 Conclusions
	Acknowledgments
	References
Chapter 8 An In-Depth Exploration of Predictive Justice with AI
	8.1 Introduction
	8.2 Predictive Justice through the Lens of Automated Decision-Making
	8.3 Predictive Justice Applications across Jurisdictions
	8.4 Observed Issues with Predictive Justice Systems
		8.4.1 Predictive Justice vs. Deliberative Justice
		8.4.2 Transparency in Predictive Justice Systems
	8.5 Solutions
		8.5.1 Response to the Challenges in Predictive Jurisprudence: A Soft Law Approach
	8.6 Vulnerable Groups, Predictive Justice, and the EU’s Artificial Intelligence Act
	8.7 Conclusion
	Acknowledgments
	References
Chapter 9 Developments on Generative AI
	9.1 Development of Generative AI
		9.1.1 Knowledge-Based Inference Engines
		9.1.2 Machine Learning
		9.1.3 Deep Learning
		9.1.4 Generative Artificial Intelligence (GAI)
	9.2 Classification of Generative AI Models
		9.2.1 Text Generation Models
		9.2.2 Image Generation Models
		9.2.3 Video Generation Models
		9.2.4 Audio Generation Models
		9.2.5 Code Generation Models
		9.2.6 Other Models
	9.3 Generative AI Applications
		9.3.1 Business
		9.3.2 Software Engineering
		9.3.3 Education
		9.3.4 Healthcare
		9.3.5 Media and Content Creation
		9.3.6 Financial Services
	9.4 Challenges with Generative AI
		9.4.1 Misuse
		9.4.2 Privacy and Security
		9.4.3 Bias
		9.4.4 Harmful or Inappropriate Content
		9.4.5 Overreliance
		9.4.6 Data Quality and Accessibility
		9.4.7 Copyright
		9.4.8 Environmental Impact
		9.4.9 Regulatory Frameworks and Policy Development
		9.4.10 Incorrect Outputs
	References
Chapter 10 Ethical Dimensions of Artificial Intelligence Balancing Innovation and Responsibility
	10.1 Artificial Intelligence
	10.2 History of Artificial Intelligence
	10.3 Artificial Intelligence Application Areas
		10.3.1 Automation-Based Industrial Production
		10.3.2 Banking and Financial Services
		10.3.3 Education
		10.3.4 Agriculture and Livestock
		10.3.5 Medicine and Health Services
		10.3.6 Public Institutions
		10.3.7 Social Media
		10.3.8 Natural Language Processing
		10.3.9 Military, Defense, and Security Areas
		10.3.10 Cybersecurity
	10.4 Artificial Intelligence and Ethics and Morals Concepts
	10.5 Ethical Concerns Raised by the Concept of Artificial Intelligence
		10.5.1 Prejudice and Justice
		10.5.2 Responsibility and Accountability
		10.5.3 Privacy and Data Security
		10.5.4 Automation and Labor Interaction
		10.5.5 Decision-Making and Transparency
		10.5.6 Balance of Power and Unfair Competition
	10.6 Predictive Justice with AI Concepts, and Cope with Their Problems
	10.7 Conclusions and the Future of Predictive Justice with AI
	References
Chapter 11 Integrating Cybersecurity in the Design and Implementation of Intelligent and Sustainable Manufacturing Systems
	11.1 Introduction
		11.1.1 Definition of Intelligent and Sustainable Manufacturing
		11.1.2 The Importance of Cybersecurity in Intelligent and Sustainable Manufacturing
		11.1.3 The Importance of Cybersecurity in Intelligent and Sustainable Manufacturing Systems
		11.1.4 Future Directions and Challenges
	11.2 Understanding the Threat Landscape
		11.2.1 Types of Cybersecurity Threats Faced by Manufacturing Systems
		11.2.2 Identification of Critical Assets and Potential Vulnerabilities
		11.2.3 Vulnerabilities in Intelligent and Sustainable Manufacturing
		11.2.4 Best Practices for Cybersecurity in Intelligent and Sustainable Manufacturing
	11.3 Cybersecurity Requirements in the Design of Intelligent and Sustainable Manufacturing Systems
		11.3.1 Secure Architecture Design Principles
		11.3.2 Security by Design (SBD) Approach
		11.3.3 Integration of Cybersecurity in the System Development Life Cycle (SDLC)
		11.3.4 Compliance with Cybersecurity Standards and Regulations
	11.4 Cybersecurity Controls in the Implementation of Intelligent and Sustainable Manufacturing Systems
		11.4.1 Access Control and Identity Management
		11.4.2 Network Security and Segmentation
		11.4.3 End Point Protection and Security Monitoring
		11.4.4 Incident Response and Disaster Recovery
	11.5 Training and Awareness for Manufacturing Personnel
		11.5.1 Training on Cybersecurity Policies and Procedures
		11.5.2 Developing a Culture of Cybersecurity Awareness
		11.5.3 Regular Testing and Simulation of Cyberattacks
	11.6 Continuous Improvement and Adaptation
		11.6.1 Regular Assessment of Cybersecurity Risks
		11.6.2 Monitoring of Emerging Threats and Vulnerabilities
		11.6.3 Updating and Improving Cybersecurity Controls and Policies
		11.6.4 Implementing a Continuous Improvement Process
	11.7 Results and Discussion
	11.8 Conclusion
	References
Chapter 12 An Invisible Threat to the Security of Nations in the Age of “Deepfakes”
	12.1 Introduction
	12.2 What Are Deepfakes?
	12.3 Devastating and Invisible Impact of Deepfakes on Security and Sovereignty
		12.3.1 Deepfake Audio or Video That Shows Racist, Abusive, Anti-Religious, and Violent Comments by a Political Leader Leading to Disturbance of Internal Peace
		12.3.2 Cyberattacks
		12.3.3 Deepfake Ransomware
		12.3.4 Cyberbullying
		12.3.5 Phishing
	12.4 International Conflicts
		12.4.1 Falsifying Order
		12.4.2 Sowing Confusion
		12.4.3 Discrediting Leaders
	12.5 A Look into the War between Deepfakes and Indian Legislations
		12.5.1 National Security Act
		12.5.2 Information Technology Act
	12.6 Comparison with Other Major Nations
		12.6.1 United States of America
		12.6.2 China
	12.7 Suggestions and the Role of the Indian Computer Emergency Team (CERT-In)
	12.8 Conclusion
	References
Index