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Digital Immune System

Principles and Practices

Edited by Sujata Priyambada Dash, Vaibhav Mishra, Bijeta Shaw, Sandeep Kumar Panda and S. Balamurugan
Series: Leading-Edge Breakthroughs in Artificial Intelligence
Copyright: 2025   |   Expected Pub Date:2025/09/30
ISBN: 9781394383757  |  Hardcover  |  
403 pages

One Line Description
Equip yourself with the knowledge to build a resilient digital infrastructure by understanding how the digital immune system leverages advanced technologies to proactively defend against cyber threats.

Audience
Research scholars in computer science and AI, IT professionals, network administrators, cybersecurity and blockchain technology experts, engineering students and government research agencies looking to the future of cybersecurity.

Description
The concept of the digital immune system represents a significant advancement in cybersecurity, reflecting the industry’s shift toward more intelligent and adaptive defense mechanisms. Drawing inspiration from biological immune systems, the digital immune system offers a solution that naturally adapts and responds to evolving threats. This book explores this evolving landscape, focusing on the integration of advanced technologies like artificial intelligence, machine learning, and automation to build resilient digital infrastructures. It delves into how these technologies can create a self-sustaining ecosystem that detects, responds to, and mitigates cyber threats in real-time and highlights the significance of predictive analytics and behavioral analysis in identifying potential threats before they materialize. Through case studies and real-world examples, the book demonstrates how organizations have successfully implemented digital
immune systems to protect their assets and maintain operational integrity in an increasingly hostile digital environment. Additionally, the book addresses the challenges and ethical considerations involved in deploying a digital immune system. It discusses the balance between security and privacy, the potential
for false positives, and the need for transparency in automated decision-making processes. By providing a comprehensive overview of the current state and prospects of digital immunity, the book serves as a crucial resource for cybersecurity professionals, IT leaders, and anyone interested in understanding the next-generation of digital defense mechanisms.
Readers will find the book: Introduces the emergence of the digital immune system; Discusses different applications of the digital immune system across various industries; Comprehensively covers the fundamentals of the digital immune system for different domains, presenting state-of the-art analysis and real-world
case studies; Examines the importance of a proactive approach to cybersecurity, emphasizing the need for organizations to move beyond traditional reactive measures.

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Author / Editor Details
Sujata Priyamada Dash, PhD is an Assistant Professor in the Department of Management at the Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India. She has published one edited book, several book chapters, and numerous articles in international journals and conferences.

Vaibhav Mishra, PhD is an Associate Professor at the ICFAI Business School Hyderabad, Telangana, India. He has published research articles in international journals of repute and edited books on blockchain, AI, and machine learning.

Bijeta Shaw, PhD is an Assistant Professor in the Operations and IT Department at ICFAI Business School Hyderabad, Telangana, India. She has authored numerous research articles in international journals and coordinated conferences.

Sandeep Kumar Panda, PhD is a Professor and the Associate Dean in the School of Science and Technology at the ICFAI Foundation for Higher Education Hyderabad, Telangana, India. He has published six edited books, several book chapters, and more than 80 articles in international journals and conferences.

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Table of Contents
Series Preface
Preface
Acknowledgements
Part 1: Digital Immune System: Principles
1. Digital Immune System Approach Toward the Impact of Gig Faculty on Organizational Learning Within Higher Education Institutes
Nimisha Singh, Sonam Gupta and Anshu Yadav
1.1 Introduction
1.2 Literature Review
1.3 Methodology
1.3.1 Quantitative Phase: Surveying the Landscape of Gig Faculty Engagement
1.3.2 Quality Assurance Mechanisms
1.3.3 Qualitative Phase: Exploring Lived Experiences and Perspectives
1.3.4 Purposive Sampling and Participant Selection
1.3.5 Focus Group Discussions: Exploring Key Themes
1.3.6 Thematic Analysis: Rediscovering Patterns and Insights
1.3.7 Data Analysis and Triangulation: Combination of Quantitative and Qualitative Findings
1.3.8 Quantitative Insights: Correlations and Variations
1.3.9 Qualitative Inferences: Threats and Opportunities
1.4 Discussion and Conclusion
1.4.1 Building an Enabling Ecosystem for Knowledge Exchange and Co-Creation
1.5 Conclusion: Underinvestment in Training, Professional Development, and Quality Assurance
1.6 Future Scope
References
2. The Economics of Implementing Digital Immune Systems
Ritesh Kumar Dubey and Prince Bhatia
2.1 Introduction
2.2 Economics of Implementing a Digital Immune System
2.3 Evolving Landscape of Digital Immune Systems
2.4 Conclusion
References
3. Blockchain-Based Digital Immune System for IoT Security with Adaptive Threat Detection and Automated Response
Chandra Priya Jayabal and Sujata Priyambada Dash
3.1 Introduction
3.2 Essential DIS Core Concepts
3.3 Related Works
3.4 Methodology
3.4.1 Decentralized Virus Analysis System
3.4.2 Consortium Blockchain Network
3.4.3 Internet of Things Sub-Networks (sidechains)
3.4.3.1 Sidechain as a Scaling Solution
3.4.4 Adaptive Threat Detection Engine
3.5 Experimental Setup
3.6 Conclusion and Future Scope
References
4. Blockchain Technology’s Potential Use in Decentralized Financial Services
Dileep Kumar Murala
4.1 Introduction
4.1.1 Blockchain
4.1.2 Need for Blockchain
4.1.3 The Rise of Decentralized Financial Systems
4.2 Related Works
4.2.1 The Emergence of Blockchain Technology
4.2.2 Blockchain Technology in Finance
4.2.3 Bibliometric Studies
4.2.4 Trade Finance
4.2.5 Blockchain Technology to Solve Trade Finance Trust Issues
4.3 Decentralized Finance Promises
4.3.1 Decentralization
4.3.2 Innovativeness
4.3.3 Interoperability
4.3.4 Borderlessness
4.3.5 Transparency
4.4 The Main Business Models in Decentralized Finance
4.4.1 Decentralized Currencies
4.4.2 Services for Dispersed Payment
4.4.3 Decentralized Fundraising
4.4.4 Decentralized Contracting
4.5 Tools, Methods, Services, and Blockchain-Based Financial Services Applications
4.5.1 Financial Services Blockchain Tools and Strategies
4.5.2 Several Blockchain Technology-Related Highlighted Services in the Financial Industry
4.5.3 Blockchain Technology Applications in Finance Service
4.6 Research Proposition
4.6.1 Blockchain-Enabled Financial Sector Benefits
4.6.1.1 People
4.6.1.2 Organization
4.6.1.3 Tech
4.6.1.4 Economics
4.6.2 Blockchain-Enabled Financial Sector Challenges
4.6.2.1 Financial Issues
4.6.2.2 Regulation Issues
4.6.2.3 Operations Issues
4.6.2.4 Adoption Issues
4.6.3 Blockchain-Enabled Financial Sector Functions
4.6.3.1 P2P Transmission
4.6.3.2 Data Ownership
4.6.3.3 Promotes Data Sharing
4.6.3.4 Distributed Financial Transaction Innovations
4.7 Limitations and Feature Scope
4.7.1 Limitations
4.7.2 Future Scope
4.8 Conclusion
References
5. A Self-Tuning Digital Immune Cybersecurity Model for Manufacturing Industry 4.0
Vasamsheti Adarsh, Sashikala Parimi and Vaibhav Mishra
5.1 Introduction: Cybersecurity and Manufacturing Industry 4.0 in the Fourth Industrial Revolution
5.2 Significant Cybersecurity Challenges in Manufacturing Industry 4.0
5.3 Increased Attack Surface
5.4 Legacy Systems and Insecure Networks
5.5 Third Industrial Revolution Machine Control Systems – Industrial Control Systems and Supervisory Control and Data Acquisition Security
5.6 Supply Chain Vulnerabilities
5.7 Virus
5.8 Types of Malwares
5.9 Data Privacy and Intellectual Property Protection
5.10 Insider Threats
5.11 Challenging Stint for Cybersecurity in Manufacturing Industry 4.0
5.12 Self-Tuning Model
5.13 Self-Tuning Model Application and Functionality
5.14 Self-Tuning Model and Industry 4.0
5.15 Applications for Self-Tuning Models in Manufacturing Industry 4.0
5.16 Self-Tuning Model and Cybersecurity
5.17 Digital Immune System
5.18 Key Roles of Cybersecurity in the Digital Immune System
5.19 Self-Tuning Model Integrated into a Digital Immune System
5.20 Proposed Digital Immune Model
5.21 Conceptual Model Integrating Digital Immune Systems, Self-Tuning Models, Cybersecurity, and Manufacturing Industry 4.0
5.22 Interdependence of Cybersecurity, Self-Tuning Model, and Digital Immune System
5.23 Conclusion
References
Part 2: Digital Immune System: Applications
6. Integrating GANs for Enhanced Phishing Detection in Digital Immune Systems
Sherwin Akshay J. G., Hari Varshan S. R., Radhika G. and Radhika N.
6.1 Introduction
6.1.1 The Escalating Risk of Phishing Attacks
6.1.2 The Importance of Advanced Cybersecurity Solutions
6.1.3 How Generative Adversarial Networks Enhance Digital Immune Systems
6.1.4 Role of Generative Adversarial Networks in Cybersecurity
6.1.5 Purpose of the Chapter
6.2 Literature Review
6.2.1 Understanding Phishing Attacks
6.2.2 Parallels Between Biological and Digital Immune Systems
6.2.2.1 How Rule-Based Systems Work
6.2.2.2 Limitations of Traditional Methods
6.2.3 Real-Time Threat Detection and Response
6.2.3.1 Key Mechanisms
6.2.3.2 Benefits
6.3 Rise of Machine Learning in Cybersecurity
6.3.1 Enhancing Phishing Detection with Machine Learning
6.3.2 Applications for Machine Learning in Phishing Detection
6.4 Proposed Methodology
6.5 Comparative Analysis with Traditional Methods
6.5.1 Rule-Based Systems
6.5.1.1 Limitations of Rule-Based Systems
6.5.2 Standard Machine Learning Models
6.5.2.1 Limitations of Standard ML Models
6.5.3 Generative Adversarial Network-Enhanced Digital Immune System Approach
6.5.3.1 Advantages of Generative Adversarial Network-Enhanced Digital Immune System
6.6 Performance Evaluation and Benchmarking
6.6.1 Key Evaluation Metrics
6.6.1.1 Accuracy and Precision
6.6.1.2 False Positive and False Negative Rates
6.6.1.3 Detection Time (Latency)
6.6.2 Experimental Setup
6.6.2.1 Dataset Composition
6.6.2.2 Training Models
6.6.2.3 Test Environment
6.6.3 Benchmarking Against Traditional Systems
6.6.4 Key Insights from Benchmarking
6.6.4.1 Highest Accuracy
6.6.4.2 Real-Time Performance
6.6.4.3 Reduced False Positives
6.6.4.4 Adaptability
6.7 Challenges and Future Trends
6.7.1 Challenges of Integrating Generative Adversarial Networks with Digital Immune Systems
6.7.1.1 High Computational Requirements
6.7.1.2 Risk of Adversarial Attacks
6.7.2 Future Trends in Enhanced Cybersecurity
6.7.2.1 Federated Learning for Better Privacy
6.8 Results and Discussion
6.8.1 Improved Detection Accuracy
6.8.2 Reduction of False Positives
6.8.3 Faster Response Times
6.8.4 Adaptability to New Threats
6.8.5 Practical Impact
6.8.6 Challenges and Future Directions
6.9 Conclusion
References
7. Managing Complexity in Cybersecurity: The Necessity of Human Oversight in Digital Immune Systems from Behavioral Forensic Perspective
Bhartrihari Pandiya and Prasad Kulkarni
7.1 Introduction
7.1.1 Role of Human Oversight in Cybersecurity
7.1.2 Significance of the Study
7.2 Literature Review
7.3 Case Studies Highlighting Human Oversight
7.3.1 Twitter Bitcoin Scam (2020)
7.3.2 SolarWinds Cyberattack of 2020
7.4 Proposed Model
7.5 Conclusion
7.6 Managerial Implications
References
8. Ontologically Structured Methods for Evaluating Semantic Textual Similarity in Security Applications
Atul Gupta, Rohit Saxena, Vishal Nagar and Satyasundara Mahapatra
8.1 Introduction
8.2 Related Work Based on Topological Methodology
8.3 Methods of Semantic Similarity Computation
8.3.1 Knowledge-Based Similarity
8.3.1.1 Node-Based or Information Content Similarity
8.3.2 Edge-Based Approach
8.4 Hybrid Approach
8.4.1 Corpus-Based Similarity
8.5 String-Based Similarity
8.5.1 Similarity Based on Character
8.5.2 Similarity Based on Levenshtein Distance
8.5.3 Similarity Based on Needleman–Wunsch
8.5.4 Similarity Based on Smith–Waterman
8.6 Similarity Based on Terms
8.6.1 Cosine-Based Similarity
8.6.2 Similarity Based on Euclidean Distance
8.6.3 Jaccard Similarity
8.7 Proposed Methodology
8.8 Results
8.9 Software Used for Computing Semantic Similarity
8.10 Conclusion
References
9. Building Human-Centric Cyber Resilience – The Role of HR Practices
Preshita Neha Tudu, Aparna Rani, Steffi L. and Chavali Akhila
9.1 Introduction
9.2 Cybersecurity and Cyber Resilience – Different or Same?
9.3 Does Cyber Resilience Bolster an Organization’s Cybersecurity?
9.4 The Evolving Role of Human Resources in Cyber Resilience and Data Protection
9.4.1 Human Resource’s Digital Transformation in the 1990s and Early 2000s
9.4.2 Digitally Focused Growth (Mid-2000s to 2010)
9.4.3 Advanced Security Actions (2015 to 2020)
9.4.4 Combining Cyber Resilience and Human Resource Strategies (2020 to Present)
9.5 The Role of Human Resources in Building Cyber Resilient Organizations
9.5.1 Recruitment and Selection
9.5.2 Training and Development
9.5.3 Policy Development and Communication
9.5.4 Employee Compensation
9.5.5 Cyber-Resilient Organizational Culture
9.5.6 Employee Offboarding
9.6 The Future and Challenges of Human Resources and Cyber Resilience
9.6.1 Building Cybersecurity Awareness among Employees
9.6.2 Recruiting and Retaining Cybersecurity Talent
9.6.3 Ensuring Data Privacy and Data Protection
9.6.4 Creating a Cybersecurity Culture
9.6.5 Adapting to Regulatory Changes and Compliance Requirements
9.7 Conclusion
References
10. Blockchain-Based Cybersecurity: A New Era of Data Protection
Sagiraju Harinadharaju, Manjunadh Muvva, Bvv Satyanarayana, Rithish Abinav and Pooja Mishra
10.1 Introduction
10.1.1 Background and Motivation
10.1.2 Limitations of Traditional Security Models
10.1.3 Scope and Objectives
10.2 Fundamentals of Blockchain Technology
10.2.1 Historical Context and Evolution
10.2.2 Core Components and Architecture
10.2.3 Consensus Mechanisms
10.2.4 Cryptographic Security
10.2.5 Smart Contracts and Automation
10.2.6 Technical Diagrams and System Architecture
10.2.7 Mathematical and Theoretical Models
10.3 Blockchain for Data Security
10.3.1 Decentralized Authentication and Identity Management
10.3.2 Access Control Mechanisms
10.3.2.1 Role-Based and Attribute-Based Controls
10.3.2.2 Blockchain-Based Credential Verification and Access Control
10.3.3 Intrusion Detection and Prevention Systems
10.3.4 Secure Data Storage and Sharing
10.4 Real-World Case Studies and Applications
10.4.1 Healthcare Data Security
10.4.2 Financial Services and Fraud Prevention
10.4.3 Supply Chain and Internet of Things Security
10.5 Integration with Emerging Technologies
10.5.1 Blockchain and Artificial Intelligence
10.5.2 Blockchain and the Internet of Things
10.5.3 Blockchain in Cloud and Edge Computing
10.6 Economic, Environmental, and Social Implications
10.6.1 Cost-Benefit Analysis of Blockchain Security
10.6.2 Energy Consumption and Environmental Impact
10.6.3 Social Trust and Decentralization Ethics
10.7 Regulatory, Legal, and Compliance Considerations
10.7.1 Data Privacy Regulations and Blockchain
10.7.2 Legal Frameworks and Governance Models
10.7.3 International Standards and Best Practices
10.8 Challenges and Future Research Directions
10.8.1 Scalability and Performance Issues
10.8.2 Quantum Computing Threats and Post-Quantum Cryptography
10.8.3 Integration with Legacy Systems
10.8.4 Research Gaps and Open Questions
10.9 Conclusions and Future Outlooks
10.9.1 Summary of Key Findings
10.9.2 The Future Role of Blockchain in Data Security
10.9.3 Recommendations for Practitioners and Researchers
References
Part 3: Digital Immune System: Novel Practices
11. Blockchain Technology and Intelligent Networking for the Metaverse
Dileep Kumar Murala, Pradosh Kumar Gantayat, Sandeep Kumar Panda and K. Vara Prasada Rao
11.1 Introduction
11.2 Blockchain for the Metaverse
11.2.1 An Overview of Blockchain Technology
11.2.1.1 What is the Significance of Blockchain?
11.2.2 Benefit of Blockchain
11.2.3 Blockchain-Based Metaverse
11.2.4 Difficulties and Discourse
11.3 Review of Existing Literature
11.4 Smart Network Architecture Using Blockchain
11.4.1 Network Design for Long Term Evolution
11.4.2 Smart Blockchain-Powered Distributed Mobile Network Infrastructure
11.4.3 Mobile Network Smart Contract Application
11.4.4 Blockchain-Based Unlicensed Spectrum Sharing
11.5 Blockchain Meets Intelligent Networking in the Metaverse
11.5.1 Blockchain-Enabled Communication
11.5.2 Blockchain-Enabled Computing
11.5.3 Device Coordination
11.5.4 Efficient Consensus and Broadcast
11.5.5 Enhance Blockchain Scalability
11.5.6 Discussion, Challenges, and Massive, Distributed Computing
11.6 Challenges and Future Scope
11.7 Conclusion
References
12. Role of AI in Digital Immune Systems
Sanjay Fuloria
12.1 Introduction
12.2 Origin of Digital Immune Systems
12.3 Underlying Principles of Digital Immune Systems
12.4 Artificial Intelligence’s Expanding Role in Cybersecurity
12.5 Key Machine Learning Approaches in Digital Immune Systems
12.6 Deep Learning and Advanced Threat Identification
12.7 Artificial Immune Systems and Intrusion Detection
12.8 Real-Time Threat Intelligence and Automated Orchestration
12.9 Practical Examples and Case Studies
12.10 Core Implementation Challenges
12.11 Regulatory Constraints
12.12 Emerging Horizons and Research Directions
12.13 Federated Learning and Edge-Based AI
12.14 Harmonizing Automated Systems and Human Expertise
References
13. AI-Powered Cybersecurity for Next-Generation Threats
Suryadeep Kumar Mahto, Bharat Singh, Nidhi Kushwaha and Rajiv Kumar
13.1 Introduction
13.2 Overview of Digital Immune Systems
13.2.1 The Role of Machine Learning in Enhancing Digital Immunity
13.2.2 Evolution of Cybersecurity: From Traditional to Artificial Intelligence-Driven Approach
13.2.3 The Need for Intelligent Cybersecurity
13.2.4 Biological Inspiration for Digital Immune Systems
13.2.5 Real-World Applications in Network Security
13.3 Key Machine Learning Algorithms for Digital Immunity
13.3.1 Anomaly Detection Algorithm
13.3.1.1 Isolation Forests
13.3.2 Classification and Threat Identification
13.3.3 Reinforcement Learning for Adaptive Defense
13.3.3.1 Q-Learning
13.4 Key Artificial Intelligence-Driven Capabilities in Digital Immune Systems
13.4.1 Threat Detection and Anomaly Recognition
13.4.1.1 Identifying Unusual Patterns in Network Traffic
13.4.1.2 Detecting Zero-Day Attacks and Advanced Persistent Threats
13.5 Case Studies: Machine Learning-Powered Intrusion Detection Systems
13.5.1 Healthcare
13.5.2 Finance
13.5.3 Critical Infrastructure
13.6 Conclusion
References
14. Building Adaptive Digital Immune Systems: A Framework for Large‑Scale Organizational Resilience
Shikha Gupta, Rajeev Kumar Ray, Amit Singh and Anuj Pal Kapoor
14.1 Introduction
14.2 Framework to Outcomes: Measuring Digital Immune Systems Effectiveness
14.2.1 Operational Resilience
14.2.2 Adaptive Threat Response
14.2.3 Regulatory Compliance at Scale
14.2.4 Sustainable Security Economics
14.2.5 Digital Trust Acceleration
14.3 Dimensions of Scalability in Digital Immune Systems
14.4 Architectural Principles for Scalable Digital Immune Systems
14.4.1 Modularity and Component-Based Design
14.4.2 Service-Oriented Architectures and Application Programming Interface-First Strategies
14.4.3 Zero-Trust Architectures at the Global Scale
14.5 Data Governance and Analytics at Scale
14.6 Organizational Structures and Governance for Scaled Digital Immune Systems
14.7 Implementation Strategies for Enterprise-Scale Digital Immune Systems
14.8 Adapting Digital Immune Systems to Future Challenges and Technological Shifts
14.9 Conclusion
References
15. Blockchain-Based Drug Authentication: Leveraging zk-SNARKs and IPFS for Enhanced Security
R. M. Sabriesh Ram Kumar, L.R.S. Harjith, Binil Rohaan, Raghul Gandhi and Pooja Mishra
15.1 Introduction
15.1.1 Background and Motivation
15.1.2 Limitations of Traditional Supply Chain Models
15.1.3 Scope and Objectives
15.2 Understanding Blockchain
15.2.1 Key Features
15.2.2 Components of Blockchain
15.2.3 Consensus Mechanisms
15.3 Security in Digital Systems
15.3.1 Confidentiality, Integrity, and Availability
15.3.2 Common Security Threats
15.4 Data Security in Blockchain
15.4.1 Cryptographic Hashing
15.4.2 Encryption and Digital Signatures
15.4.3 Consensus Mechanisms for Security
15.4.4 Challenges in Blockchain Security
15.5 Introduction to Interplanetary File Systems
15.5.1 How Interplanetary File Systems Work
15.5.2 Benefits of Interplanetary File Systems over Traditional Storage
15.5.3 Integration of Interplanetary File Systems with Blockchain
15.6 Introduction to Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge
15.6.1 How Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge Work
15.6.2 Benefits of Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge over Traditional Verification
15.6.3 Integration of Zero-Knowledge Succinct Non‑Interactive Arguments of Knowledge with Blockchain in Pharmaceutical Supply Chain
15.7 Need for Blockchain in Drug Traceability
15.7.1 Problems with the Existing Drug Supply Chain
15.7.2 Counterfeit Drugs and Their Impact
15.7.3 How Blockchain Solves these Issues
15.8 Implementation of Blockchain-Based Drug Traceability System
15.8.1 System Architecture Overview
15.8.2 Smart Contracts for Drug Verification
15.8.3 Frontend and Web3 Integration
15.8.4 Integration of Zero-Knowledge Succinct Non‑Interactive Arguments of Knowledge, Verifiable Credentials, and Interplanetary File Systems
15.8.4.1 Algorithm for Secure Order Processing
15.8.4.2 Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge (zk-SNARKs)
15.8.4.3 Verifiable Credentials
15.8.4.4 Interplanetary File System
15.8.5 Supply Chain Workflow
15.9 Advantages and Challenges of Blockchain in Drug Traceability
15.9.1 Efficiency and Performance Metrics
15.9.2 Benefits
15.9.3 Challenges
15.10 Future Scope
15.10.1 Artificial Intelligence-Based Analytics
15.10.2 Integration with the Internet of Things
15.10.3 Advanced Smart Contracts
15.10.4 Cross-Industry Collaboration
15.10.5 Scalability and Efficiency Improvements
References
16. Privacy-Preserving and Scalable Authentication Using zk-SNARK‑Based ZKP Blockchain PKI
Amrutanshu Panigrahi, Bibhuprasad Sahu, Abhilash Pati and Subrata Chowdhury
16.1 Introduction
16.2 Literature Survey
16.3 Background Study
16.3.1 Public Key Infrastructure
16.3.2 Blockchain-Based Public Key Infrastructure
16.3.3 Zero-Knowledge Proof Consensus Mechanism
16.4 Proposed Methodology
16.4.1 Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge
16.4.2 Zero-Knowledge Succinct Non-Interactive Arguments in Zero Knowledge Proof-Based Blockchain Public Key Infrastructure
16.4.3 Ganache Truffle Suite
16.5 Workflow of the Proposed Public Key Infrastructure
16.6 Result and Analysis
16.7 Conclusion
References
Index

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