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Submit a ProposalCognitive Cyber Crimes in the Era of Artificial Intelligence
 | Edited by Rajesh Kumar Chakrawarti, Romil Rawat, Kriti Bhaswar Singh, A. Samson Arun Raj, Abhishek Singh, Hitesh Rawat, and Anjali Rawat Copyright: 2025 | Expected Pub Date:2025// ISBN: 9781394386543 | Hardcover | 534 pages Price: $225 USD  |
One Line Description
Protect your organization from next-generation threats with this comprehensive analysis of cognitive cybercrimes, addressing future legal, ethical, and policy challenges in the age of AI.
Audience
Academics, cybersecurity professionals, digital forensic experts, law enforcement and intelligence agencies, AI and machine learning researchers, and healthcare and neurotechnology experts
Academics, cybersecurity professionals, digital forensic experts, law enforcement and intelligence agencies, AI and machine learning researchers, and healthcare and neurotechnology experts
Description
Cognitive Cyber Crimes in the Era of Artificial Intelligence explores the emerging dimension of cybercrime where artificial intelligence, neuroscience, and cryptography intersect. It introduces the concept of neurocryptic forensics, a novel framework for investigating AI-driven psychological manipulations, deepfake-induced fraud, cognitive hacking, and brainwave-targeted cyber-attacks. As digital threats evolve, cybercriminals are shifting from traditional hacking methods to exploiting human cognition. This book provides a comprehensive analysis of cognitive cybercrime techniques and equips readers with methodologies to detect, prevent, and mitigate such threats. It serves as a guide for researchers, cybersecurity professionals, forensic analysts, policymakers, and AI developers who aim to secure both digital infrastructures and human perception against next-generation cyber threats.
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Cognitive Cyber Crimes in the Era of Artificial Intelligence explores the emerging dimension of cybercrime where artificial intelligence, neuroscience, and cryptography intersect. It introduces the concept of neurocryptic forensics, a novel framework for investigating AI-driven psychological manipulations, deepfake-induced fraud, cognitive hacking, and brainwave-targeted cyber-attacks. As digital threats evolve, cybercriminals are shifting from traditional hacking methods to exploiting human cognition. This book provides a comprehensive analysis of cognitive cybercrime techniques and equips readers with methodologies to detect, prevent, and mitigate such threats. It serves as a guide for researchers, cybersecurity professionals, forensic analysts, policymakers, and AI developers who aim to secure both digital infrastructures and human perception against next-generation cyber threats.
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Author / Editor Details
Rajesh Kumar Chakrawarti, PhD is a Professor and the Director at the Sushila Devi Bansal College of Technology in the Bansal Group of Institutes, Indore with more than 21 years of academic and industry experience. He has attended more than 100 conferences and published more than 100 research papers, book chapters, and abstracts in national and international journals and conferences. His research areas include compiler design, natural language processing, computational linguistics, machine translation, and word-sense disambiguation.
Rajesh Kumar Chakrawarti, PhD is a Professor and the Director at the Sushila Devi Bansal College of Technology in the Bansal Group of Institutes, Indore with more than 21 years of academic and industry experience. He has attended more than 100 conferences and published more than 100 research papers, book chapters, and abstracts in national and international journals and conferences. His research areas include compiler design, natural language processing, computational linguistics, machine translation, and word-sense disambiguation.
Romil Rawat is a researcher at the Research Laboratory in Geomatics and Information Systems, part of the National Research Council in Rome and a Professor at Shri Vaishnav Vidyapeeth Vishwavidyalaya. He has published more than 15 research papers in international journals and conferences and more than ten books. His work focuses on the development of state-of-the-art machine learning algorithms aimed at detecting, predicting, and mitigating criminal activities across social networks.
Kriti Bhaswar Singh, PhD is an Associate Professor in the Department of Commerce and Financial Studies in the School of Management Sciences at the Central University of Jharkhand with more than 20 years of teaching and corporate experience. He has published four books and 36 research papers and book chapters on various areas of finance in refereed journals and presented 23 papers in various conferences. His research focuses on the capital market, corporate finance, and valuations.
A. Samson Arun Raj, PhD is an Assistant Professor and Internal Placement Coordinator in the Division of Computer Science and Engineering in the School of Computer Science and Technology at the Karunya Institute of Technology and Sciences. He has published more than 25 articles in international journals and conferences of repute. He is engaged in cutting-edge research for smart city development, focusing on drone networks and energy grid applications.
Abhishek Singh, PhD is the Director of the Rajiv Academy for Technology and Management with more than 22 years of teaching experience. He has published more 22 research papers in international journals and presented an additional 30 at international conferences. His teachings focus on accounting and finance.
Hitesh Rawat is a PhD Research scholar at Shri Vaishnav Vidyapeeth Vishwavidyalaya University with more that eight years of experience. He has chaired international conferences and hosted several research events, including national and international research schools, PhD colloquia, workshops, and training programs. His work focuses on business frameworks for secure communication and cybersecurity.
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Table of Contents
Preface
1. Intersection of AI, Neuroscience, and Cryptography in Cybercrime Investigations
Priya Matta, Dhiren P. Bhagat, Priyanka Rastogi, Anisha and Atika Gupta
1.1 Introduction
1.2 Related Work
1.3 Proposed Work
1.4 Results
1.5 Analysis
1.6 Discussion
1.7 Conclusion
1.8 Future Work
References
2. Detecting and Preventing Synthetic Identity Fraud and Mapping
Davinder Singh Gill, Mirza Shuja, Tapan Kant and Mukesh Kumar
2.1 Introduction
2.2 Related Work
2.3 Proposed Work
2.4 Results
2.5 Analysis
2.6 Discussion
2.7 Conclusion and Future Work
References
3. AI-Generated Propaganda and Automated Misinformation Warfare
Romil Rawat
3.1 Introduction
3.2 Related Work
3.3 Proposed Work
3.4 Results
3.5 Analysis
3.6 Discussion
3.7 Conclusion
3.8 Future Work
References
4. Techniques for Analyzing and Debunking Deepfakes
Alpesh Soni, Kamal Borana, Juber Mirza and Abhishek Sharma
4.1 Introduction
4.2 Related Work
4.3 Proposed Work
4.4 Results
4.5 Analysis
4.6 Discussion
4.7 Conclusion
4.8 Future Work
References
5. How Attackers Can Steal and Manipulate Brainwave Signals
A. Samson Arun Raj, Abhishek Singh Rathore, Juber Mirza, Ankita Chourasia and Abhishek Sharma
5.1 Introduction
5.2 Related Work
5.3 Proposed Work
5.4 Results
5.5 Analysis
5.6 Discussion
5.7 Conclusion
5.8 Future Work
References
6. Developing AI-Enhanced Forensic Tools to Combat Cognitive Cybercrimes
Priya Matta, Atika Gupta, R.K. Saini, Sopan Talekar and Manjusha Tatiya
6.1 Introduction
6.2 Related Work
6.3 Proposed Work
6.4 Results
6.5 Analysis
6.6 Discussion
6.7 Conclusion
6.8 Future Work
References
7. Social Engineering in the AI Era: Exploiting Human Perception for Threat
Sunil Parihar, Ankit Jain, Rahul Verma, Rupa Rajoriya and Kapil Bhardwaj
7.1 Introduction
7.2 Related Work
7.3 Proposed Work
7.4 Results
7.5 Analysis
7.6 Discussion
7.7 Conclusion
7.8 Future Work
References
8. Understanding Cognitive Vulnerabilities and Psychological Hacking Techniques
Anjali Rawat and Anand Rajavat
8.1 Introduction
8.2 Related Work
8.3 Proposed Work
8.4 Results
8.5 Analysis
8.6 Discussion
8.7 Conclusion
8.8 Future Work
References
9. AI-Powered Misinformation Campaigns and Subliminal Influence Tactics
Rajesh Kumar Chakrawarti, A. Samson Arun Raj, Alpesh Soni and Sachin Chirgaiya
9.1 Introduction
9.2 Related Work
9.3 Proposed Work
9.4 Results
9.5 Analysis
9.6 Discussion
9.7 Conclusion
9.8 Future Work
References
10. Brainwave Authentication: Threats and Vulnerabilities
Hitesh Rawat and Anand Rajavat
10.1 Introduction
10.2 Related Work
10.3 Proposed Work
10.4 Results and Tables
10.5 Analysis
10.6 Discussion
10.7 Conclusion
10.8 Future Work
References
11. Algorithmic Bias and Psychographic Profiling for Manipulation
Hitesh Rawat and Anand Rajavat
11.1 Introduction
11.2 Related Work
11.3 Proposed Work
11.4 Results
11.5 Analysis
11.6 Discussion
11.7 Conclusion
11.8 Future Work
References
12. Role of AI-Enhanced Cryptographic Techniques in Protecting Cognition
Vivek Bhardwaj, Balwinder Kaur Dhaliwal, Jeyaganesh Viswanathan, and Davinder Singh Gill
12.1 Introduction
12.2 Related Work
12.3 Proposed Work
12.4 Results
12.5 Analysis
12.6 Discussion
12.7 Conclusion
12.8 Future Work
References
13. AI-Powered Mind-Reading and Neural Exploitation Techniques
Hitesh Rawat, Anjali Rawat, Romil Rawat and Anand Rajavat
13.1 Introduction
13.2 Related Work
13.3 Proposed Work
13.4 Results
13.5 Analysis
13.6 Discussion
13.7 Conclusion
13.8 Future Work
References
14. AI-Generated Misinformation and Automated Psychological Warfare
Hitesh Rawat, Anjali Rawat and Anand Rajavat
14.1 Introduction
14.2 Related Work
14.3 Proposed Work
14.4 Results
14.5 Analysis
14.6 Discussion
14.7 Conclusion
14.8 Future Work
References
15. Analyzing Neural Forensics Data in Criminal Investigations
Priya Matta, Minit Arora, Sopan Talekar, Priyanka Rastogi and Gagan Dangwal
15.1 Introduction
15.2 Related Work
15.3 Proposed Work
15.4 Results
15.5 Analysis
15.6 Discussion
15.7 Conclusion
15.8 Future Work
References
16. Preventing Neural Data Leaks with Biometric Encryption
Antonio González-Torres
16.1 Introduction
16.2 Related Work
16.3 Proposed Work
16.4 Results
16.5 Analysis
16.6 Discussion
16.7 Conclusion
16.8 Future Work
References
17. Deepfake Forensics and Synthetic Media Attacks
Yagyanath Rimal, Rajesh Kumar Chakrawarti, Neeraj Mehta, and Alpesh Soni
17.1 Introduction
17.2 Related Work
17.3 Proposed Work
17.4 Results and Tables
17.5 Analysis
17.6 Discussion
17.7 Conclusion
17.8 Future Work
References
18. Identifying and Mitigating Psychological Bias in Cybersecurity
Yagyanath Rimal, Romil Rawat, Rajesh Kumar Chakrawarti and Abhishek Sharma
18.1 Introduction
18.2 Related Work
18.3 Proposed Work
18.4 Results
18.5 Analysis
18.6 Discussion
18.7 Conclusion
18.8 Future Work
References
19. AI-Assisted Deep Social Profiling for Cyber Exploitation
Vivek Bhardwaj, Tanima Thakur, Jeyaganesh Viswanathan and Mukesh Kumar
19.1 Introduction
19.2 Related Work
19.3 Proposed Work
19.4 Result
19.5 Analysis
19.6 Discussion
19.7 Conclusion
19.8 Future Work
References
20. Investigative Approaches for Dark Web Cognitive Cybercrimes
Anjali Rawat and Anand Rajavat
20.1 Introduction
20.2 Related Work
20.3 Proposed Work
20.4 Results
20.5 Analysis
20.6 Discussion
20.7 Conclusion
20.8 Future Work
References
21. AI-Powered Image Morphing and Watermarking Techniques for Threat Attribution
Chandrapal Singh Dangi, Abhishek Singh Rathore, Kamal Borana and Sachin Chirgaiya
21.1 Introduction
21.2 Related Work
21.3 Proposed Work
21.4 Results
21.5 Analysis
21.6 Discussion
21.7 Conclusion
21.8 Future Work
References
22. Decentralized Identity Verification: Blockchain for Cognitive Security
Mukesh Kumar, Sahil Rampal, Tapan Kant and Davinder Singh Gill
22.1 Introduction
22.2 Related Work
22.3 Proposed Work
22.4 Results
22.5 Analysis
22.6 Discussion
22.7 Conclusion
22.8 Future Work
References
23. Cognitive Cyber Crimes in the AI Era: Unraveling Digital Deception through Intelligent Data Analytics
Ashish Dibouliya
23.1 Introduction
23.1.1 Objectives
23.1.2 Problem Statement
23.2 Literature Review
23.3 Proposed Approach
23.4 Methodology
23.5 Implementation Details
23.6 Results
23.7 Discussion
23.8 Conclusion
23.9 Future Work
References
24. Forensic Insights into Cognitive Cyberattacks: Integrating Artificial Intelligence and Big Data Analytics
Romil Rawat
24.1 Introduction
24.2 Related Work
24.3 Methodology
24.3.1 Dataset Acquisition
24.3.2 Data Preprocessing
24.3.3 Feature Engineering
24.3.4 Hybrid Model Design
24.3.5 Model Training and Evaluation
24.3.6 Mathematical Modeling and Algorithm
24.3.6.1 Algorithm Pseudocode as Shown in Table 24.2
24.4 Results and Performance Evaluation
24.4.1 Quantitative Results
24.4.2 Comparative Analysis
24.4.3 Confusion Matrix Insights
24.4.4 Computational Efficiency
24.4.5 Practical Forensic Insights
24.5 Discussion
24.6 Conclusion
24.7 Future Work
References
25. Cognitive Cybersecurity for Protecting Rural Artisan E-Commerce Platforms
Devbrath, Kriti Bhaswar Singh, Neha Aggarwal and Kuntal Dutta
25.1 Introduction
25.1.1 Application of Cognitive Cybersecurity in Rural Artisan e-Commerce Platforms
25.1.2 Objectives of the Research
25.2 Related Work
25.3 Proposed Work
25.3.1 Framework Architecture
25.3.2 Algorithm
25.3.3 Dataset
25.4 Methodology
25.5 Implementation
25.6 Results
25.6.1 Classification Performance
25.6.2 Comparative Analysis
25.6.3 Latency and Scalability Evaluation
25.6.4 Robustness Under Adversarial Conditions
25.6.5 Interpretability and Trustworthiness
25.6.6 Case Study Outcomes
25.6.7 Negative Results and Limitations
25.7 Discussion
25.8 Conclusion
25.9 Future Work
References
26. Fraud and Misreporting Risks in Executive Pay: A Cognitive AI Detection Framework by Algorithmic Governance
Neha Aggarwal, Kriti Bhaswar Singh, Devbrath and Kuntal Dutta
26.1 Introduction
26.1.1 Application of the Framework
26.1.2 Objectives of the Research
26.2 Related Work
26.3 Proposed Work
26.3.1 Framework Overview
26.3.2 Mathematical Formulation
26.3.3 Flowchart
26.3.4 Dataset Description
26.3.5 Algorithm
26.4 Methodology
26.5 Implementation
26.6 Results
26.6.1 Negative Results and Limitations
26.7 Discussion
26.8 Conclusion
26.9 Future Work
References
27. Cognitive AI Systems for Real-Time Market Anomaly Detection and Asset Pricing in Financial Markets
Kuntal Dutta, Kriti Bhaswar Singh, Devbrath and Neha Aggarwal
27.1 Introduction
27.1.1 Applications of the Rapid Evolution of Financial Markets Has Intensified the Risk of Fraudulent Trading Activities, Demanding Intelligent Real-Time Detection Systems
27.1.2 Objectives of this Research
27.2 Related Work
27.3 Proposed Work
27.3.1 Dataset
27.3.2 Algorithm
27.4 Methodology
27.5 Implementation
27.6 Results
27.6.1 Negative Result
27.7 Discussion
27.8 Conclusion
27.9 Future Work
References
28. Block Chain for Detecting Financial Accounting Risk
Kriti Bhaswar Singh, Abhishek Singh, S.K. Singh and Sanjeev Gupta
28.1 Introduction
28.1.1 Applications of Blockchain in Financial Accounting Risk
28.1.2 Objectives
28.2 Related Work
28.3 Proposed Work
28.3.1 Dataset
28.3.2 Algorithm
28.4 Methodology
28.5 Implementation
28.6 Results
28.6.1 Negative Result
28.6.2 Discussion
28.6.3 Conclusion
28.6.4 Future Work
References
About the Editors
Index
Back to Top
Preface
1. Intersection of AI, Neuroscience, and Cryptography in Cybercrime Investigations
Priya Matta, Dhiren P. Bhagat, Priyanka Rastogi, Anisha and Atika Gupta
1.1 Introduction
1.2 Related Work
1.3 Proposed Work
1.4 Results
1.5 Analysis
1.6 Discussion
1.7 Conclusion
1.8 Future Work
References
2. Detecting and Preventing Synthetic Identity Fraud and Mapping
Davinder Singh Gill, Mirza Shuja, Tapan Kant and Mukesh Kumar
2.1 Introduction
2.2 Related Work
2.3 Proposed Work
2.4 Results
2.5 Analysis
2.6 Discussion
2.7 Conclusion and Future Work
References
3. AI-Generated Propaganda and Automated Misinformation Warfare
Romil Rawat
3.1 Introduction
3.2 Related Work
3.3 Proposed Work
3.4 Results
3.5 Analysis
3.6 Discussion
3.7 Conclusion
3.8 Future Work
References
4. Techniques for Analyzing and Debunking Deepfakes
Alpesh Soni, Kamal Borana, Juber Mirza and Abhishek Sharma
4.1 Introduction
4.2 Related Work
4.3 Proposed Work
4.4 Results
4.5 Analysis
4.6 Discussion
4.7 Conclusion
4.8 Future Work
References
5. How Attackers Can Steal and Manipulate Brainwave Signals
A. Samson Arun Raj, Abhishek Singh Rathore, Juber Mirza, Ankita Chourasia and Abhishek Sharma
5.1 Introduction
5.2 Related Work
5.3 Proposed Work
5.4 Results
5.5 Analysis
5.6 Discussion
5.7 Conclusion
5.8 Future Work
References
6. Developing AI-Enhanced Forensic Tools to Combat Cognitive Cybercrimes
Priya Matta, Atika Gupta, R.K. Saini, Sopan Talekar and Manjusha Tatiya
6.1 Introduction
6.2 Related Work
6.3 Proposed Work
6.4 Results
6.5 Analysis
6.6 Discussion
6.7 Conclusion
6.8 Future Work
References
7. Social Engineering in the AI Era: Exploiting Human Perception for Threat
Sunil Parihar, Ankit Jain, Rahul Verma, Rupa Rajoriya and Kapil Bhardwaj
7.1 Introduction
7.2 Related Work
7.3 Proposed Work
7.4 Results
7.5 Analysis
7.6 Discussion
7.7 Conclusion
7.8 Future Work
References
8. Understanding Cognitive Vulnerabilities and Psychological Hacking Techniques
Anjali Rawat and Anand Rajavat
8.1 Introduction
8.2 Related Work
8.3 Proposed Work
8.4 Results
8.5 Analysis
8.6 Discussion
8.7 Conclusion
8.8 Future Work
References
9. AI-Powered Misinformation Campaigns and Subliminal Influence Tactics
Rajesh Kumar Chakrawarti, A. Samson Arun Raj, Alpesh Soni and Sachin Chirgaiya
9.1 Introduction
9.2 Related Work
9.3 Proposed Work
9.4 Results
9.5 Analysis
9.6 Discussion
9.7 Conclusion
9.8 Future Work
References
10. Brainwave Authentication: Threats and Vulnerabilities
Hitesh Rawat and Anand Rajavat
10.1 Introduction
10.2 Related Work
10.3 Proposed Work
10.4 Results and Tables
10.5 Analysis
10.6 Discussion
10.7 Conclusion
10.8 Future Work
References
11. Algorithmic Bias and Psychographic Profiling for Manipulation
Hitesh Rawat and Anand Rajavat
11.1 Introduction
11.2 Related Work
11.3 Proposed Work
11.4 Results
11.5 Analysis
11.6 Discussion
11.7 Conclusion
11.8 Future Work
References
12. Role of AI-Enhanced Cryptographic Techniques in Protecting Cognition
Vivek Bhardwaj, Balwinder Kaur Dhaliwal, Jeyaganesh Viswanathan, and Davinder Singh Gill
12.1 Introduction
12.2 Related Work
12.3 Proposed Work
12.4 Results
12.5 Analysis
12.6 Discussion
12.7 Conclusion
12.8 Future Work
References
13. AI-Powered Mind-Reading and Neural Exploitation Techniques
Hitesh Rawat, Anjali Rawat, Romil Rawat and Anand Rajavat
13.1 Introduction
13.2 Related Work
13.3 Proposed Work
13.4 Results
13.5 Analysis
13.6 Discussion
13.7 Conclusion
13.8 Future Work
References
14. AI-Generated Misinformation and Automated Psychological Warfare
Hitesh Rawat, Anjali Rawat and Anand Rajavat
14.1 Introduction
14.2 Related Work
14.3 Proposed Work
14.4 Results
14.5 Analysis
14.6 Discussion
14.7 Conclusion
14.8 Future Work
References
15. Analyzing Neural Forensics Data in Criminal Investigations
Priya Matta, Minit Arora, Sopan Talekar, Priyanka Rastogi and Gagan Dangwal
15.1 Introduction
15.2 Related Work
15.3 Proposed Work
15.4 Results
15.5 Analysis
15.6 Discussion
15.7 Conclusion
15.8 Future Work
References
16. Preventing Neural Data Leaks with Biometric Encryption
Antonio González-Torres
16.1 Introduction
16.2 Related Work
16.3 Proposed Work
16.4 Results
16.5 Analysis
16.6 Discussion
16.7 Conclusion
16.8 Future Work
References
17. Deepfake Forensics and Synthetic Media Attacks
Yagyanath Rimal, Rajesh Kumar Chakrawarti, Neeraj Mehta, and Alpesh Soni
17.1 Introduction
17.2 Related Work
17.3 Proposed Work
17.4 Results and Tables
17.5 Analysis
17.6 Discussion
17.7 Conclusion
17.8 Future Work
References
18. Identifying and Mitigating Psychological Bias in Cybersecurity
Yagyanath Rimal, Romil Rawat, Rajesh Kumar Chakrawarti and Abhishek Sharma
18.1 Introduction
18.2 Related Work
18.3 Proposed Work
18.4 Results
18.5 Analysis
18.6 Discussion
18.7 Conclusion
18.8 Future Work
References
19. AI-Assisted Deep Social Profiling for Cyber Exploitation
Vivek Bhardwaj, Tanima Thakur, Jeyaganesh Viswanathan and Mukesh Kumar
19.1 Introduction
19.2 Related Work
19.3 Proposed Work
19.4 Result
19.5 Analysis
19.6 Discussion
19.7 Conclusion
19.8 Future Work
References
20. Investigative Approaches for Dark Web Cognitive Cybercrimes
Anjali Rawat and Anand Rajavat
20.1 Introduction
20.2 Related Work
20.3 Proposed Work
20.4 Results
20.5 Analysis
20.6 Discussion
20.7 Conclusion
20.8 Future Work
References
21. AI-Powered Image Morphing and Watermarking Techniques for Threat Attribution
Chandrapal Singh Dangi, Abhishek Singh Rathore, Kamal Borana and Sachin Chirgaiya
21.1 Introduction
21.2 Related Work
21.3 Proposed Work
21.4 Results
21.5 Analysis
21.6 Discussion
21.7 Conclusion
21.8 Future Work
References
22. Decentralized Identity Verification: Blockchain for Cognitive Security
Mukesh Kumar, Sahil Rampal, Tapan Kant and Davinder Singh Gill
22.1 Introduction
22.2 Related Work
22.3 Proposed Work
22.4 Results
22.5 Analysis
22.6 Discussion
22.7 Conclusion
22.8 Future Work
References
23. Cognitive Cyber Crimes in the AI Era: Unraveling Digital Deception through Intelligent Data Analytics
Ashish Dibouliya
23.1 Introduction
23.1.1 Objectives
23.1.2 Problem Statement
23.2 Literature Review
23.3 Proposed Approach
23.4 Methodology
23.5 Implementation Details
23.6 Results
23.7 Discussion
23.8 Conclusion
23.9 Future Work
References
24. Forensic Insights into Cognitive Cyberattacks: Integrating Artificial Intelligence and Big Data Analytics
Romil Rawat
24.1 Introduction
24.2 Related Work
24.3 Methodology
24.3.1 Dataset Acquisition
24.3.2 Data Preprocessing
24.3.3 Feature Engineering
24.3.4 Hybrid Model Design
24.3.5 Model Training and Evaluation
24.3.6 Mathematical Modeling and Algorithm
24.3.6.1 Algorithm Pseudocode as Shown in Table 24.2
24.4 Results and Performance Evaluation
24.4.1 Quantitative Results
24.4.2 Comparative Analysis
24.4.3 Confusion Matrix Insights
24.4.4 Computational Efficiency
24.4.5 Practical Forensic Insights
24.5 Discussion
24.6 Conclusion
24.7 Future Work
References
25. Cognitive Cybersecurity for Protecting Rural Artisan E-Commerce Platforms
Devbrath, Kriti Bhaswar Singh, Neha Aggarwal and Kuntal Dutta
25.1 Introduction
25.1.1 Application of Cognitive Cybersecurity in Rural Artisan e-Commerce Platforms
25.1.2 Objectives of the Research
25.2 Related Work
25.3 Proposed Work
25.3.1 Framework Architecture
25.3.2 Algorithm
25.3.3 Dataset
25.4 Methodology
25.5 Implementation
25.6 Results
25.6.1 Classification Performance
25.6.2 Comparative Analysis
25.6.3 Latency and Scalability Evaluation
25.6.4 Robustness Under Adversarial Conditions
25.6.5 Interpretability and Trustworthiness
25.6.6 Case Study Outcomes
25.6.7 Negative Results and Limitations
25.7 Discussion
25.8 Conclusion
25.9 Future Work
References
26. Fraud and Misreporting Risks in Executive Pay: A Cognitive AI Detection Framework by Algorithmic Governance
Neha Aggarwal, Kriti Bhaswar Singh, Devbrath and Kuntal Dutta
26.1 Introduction
26.1.1 Application of the Framework
26.1.2 Objectives of the Research
26.2 Related Work
26.3 Proposed Work
26.3.1 Framework Overview
26.3.2 Mathematical Formulation
26.3.3 Flowchart
26.3.4 Dataset Description
26.3.5 Algorithm
26.4 Methodology
26.5 Implementation
26.6 Results
26.6.1 Negative Results and Limitations
26.7 Discussion
26.8 Conclusion
26.9 Future Work
References
27. Cognitive AI Systems for Real-Time Market Anomaly Detection and Asset Pricing in Financial Markets
Kuntal Dutta, Kriti Bhaswar Singh, Devbrath and Neha Aggarwal
27.1 Introduction
27.1.1 Applications of the Rapid Evolution of Financial Markets Has Intensified the Risk of Fraudulent Trading Activities, Demanding Intelligent Real-Time Detection Systems
27.1.2 Objectives of this Research
27.2 Related Work
27.3 Proposed Work
27.3.1 Dataset
27.3.2 Algorithm
27.4 Methodology
27.5 Implementation
27.6 Results
27.6.1 Negative Result
27.7 Discussion
27.8 Conclusion
27.9 Future Work
References
28. Block Chain for Detecting Financial Accounting Risk
Kriti Bhaswar Singh, Abhishek Singh, S.K. Singh and Sanjeev Gupta
28.1 Introduction
28.1.1 Applications of Blockchain in Financial Accounting Risk
28.1.2 Objectives
28.2 Related Work
28.3 Proposed Work
28.3.1 Dataset
28.3.2 Algorithm
28.4 Methodology
28.5 Implementation
28.6 Results
28.6.1 Negative Result
28.6.2 Discussion
28.6.3 Conclusion
28.6.4 Future Work
References
About the Editors
Index
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