Himanshu Upadhyay – författare

This book highlights the applications and theory of artificial intelligence in the domain of cybersecurity.The book proposes new approaches and ideas to present applications of innovative approaches in real-time environments. In the past few decades, there has been an exponential rise in the application of artificial intelligence technologies (such as deep learning, machine learning, blockchain) for solving complex and intricate problems arising in the domain of cybersecurity. The versatility of these techniques has made them a favorite among scientists and researchers working in diverse areas.This book serves as a reference for young scholars, researchers, and industry professionals working in the field of Artificial Intelligence and Cybersecurity.

This book highlights the applications and theory of artificial intelligence in the domain of cybersecurity.

The book proposes new approaches and ideas to present applications of innovative approaches in real-time environments. In the past few decades, there has been an exponential rise in the application of artificial intelligence technologies (such as deep learning, machine learning, blockchain) for solving complex and intricate problems arising in the domain of cybersecurity. The versatility of these techniques has made them a favorite among scientists and researchers working in diverse areas.

 This book serves as a reference for young scholars, researchers, and industry professionals working in the field of Artificial Intelligence and Cybersecurity.

 

This book highlights the applications and theory of artificial intelligence in the domain of cybersecurity.The book proposes new approaches and ideas to present applications of innovative approaches in real-time environments. In the past few decades, there has been an exponential rise in the application of artificial intelligence technologies (such as deep learning, machine learning, blockchain) for solving complex and intricate problems arising in the domain of cybersecurity. The versatility of these techniques has made them a favorite among scientists and researchers working in diverse areas.This book serves as a reference for young scholars, researchers, and industry professionals working in the field of Artificial Intelligence and Cybersecurity.

This two-volume set, LNICST 685 and 686, constitutes the refereed post-conference proceedings of the 16th EAI International Conference on Digital Forensics and Cyber Crime, ICDF2C 2025, Miami, FL, USA, during November 17–19, 2025.The 66 full papers and 1 poster paper included in these volumes were carefully reviewed and selected from 163 submissions. They have been organized in the following topical sections:Part I: AI and Machine Learning in Digital Forensics: Papers applying AI, LLMs, and deep learning to detect anomalies,enhance forensics, or improve model reliability; Digital Forensics and Incident Response: Focused on forensic investigation, evidence recovery, data analysis, and structured workflows; Adversarial Machine Learning and Attack Detection: Addressing adversarial AI, attack simulation, and defensive mechanisms; and Cyber Threat Intelligence and Malware Analysis: Focus on malware detection, honeynets, phishing, traffic analysis, and intrusion defense.Part II: Cyber Threat Intelligence and Malware Analysis: Focus on malware detection, honeynets, phishing, traffic analysis, and intrusion defense; Digital Evidence Management, Blockchain, and Privacy: Addressing blockchain forensics, data provenance, and privacy-preserving computation; Critical Infrastructure and Cyber-Physical Security: Cyber resilience in physical and industrial systems, including IoT, satellites, and SCADA; Legal, Policy, and AI Governance in Digital Forensics: Studies bridging AI governance, digital law, compliance, and socio-technical policy; and Posters & Demos.

This two-volume set, LNICST 685 and 686, constitutes the refereed post-conference proceedings of the 16th EAI International Conference on Digital Forensics and Cyber Crime, ICDF2C 2025, Miami, FL, USA, during November 17–19, 2025.The 66 full papers and 1 poster paper included in these volumes were carefully reviewed and selected from 163 submissions. They have been organized in the following topical sections:Part I: AI and Machine Learning in Digital Forensics: Papers applying AI, LLMs, and deep learning to detect anomalies,enhance forensics, or improve model reliability; Digital Forensics and Incident Response: Focused on forensic investigation, evidence recovery, data analysis, and structured workflows; Adversarial Machine Learning and Attack Detection: Addressing adversarial AI, attack simulation, and defensive mechanisms; and Cyber Threat Intelligence and Malware Analysis: Focus on malware detection, honeynets, phishing, traffic analysis, and intrusion defense.Part II: Cyber Threat Intelligence and Malware Analysis: Focus on malware detection, honeynets, phishing, traffic analysis, and intrusion defense; Digital Evidence Management, Blockchain, and Privacy: Addressing blockchain forensics, data provenance, and privacy-preserving computation; Critical Infrastructure and Cyber-Physical Security: Cyber resilience in physical and industrial systems, including IoT, satellites, and SCADA; Legal, Policy, and AI Governance in Digital Forensics: Studies bridging AI governance, digital law, compliance, and socio-technical policy; and Posters & Demos.

This two-volume set, LNICST 685 and 686, constitutes the refereed post-conference proceedings of the 16th EAI International Conference on Digital Forensics and Cyber Crime, ICDF2C 2025, Miami, FL, USA, during November 17–19, 2025.The 66 full papers and 1 poster paper included in these volumes were carefully reviewed and selected from 163 submissions. They have been organized in the following topical sections:Part I: AI and Machine Learning in Digital Forensics: Papers applying AI, LLMs, and deep learning to detect anomalies,enhance forensics, or improve model reliability; Digital Forensics and Incident Response: Focused on forensic investigation, evidence recovery, data analysis, and structured workflows; Adversarial Machine Learning and Attack Detection: Addressing adversarial AI, attack simulation, and defensive mechanisms; and Cyber Threat Intelligence and Malware Analysis: Focus on malware detection, honeynets, phishing, traffic analysis, and intrusion defense.Part II: Cyber Threat Intelligence and Malware Analysis: Focus on malware detection, honeynets, phishing, traffic analysis, and intrusion defense; Digital Evidence Management, Blockchain, and Privacy: Addressing blockchain forensics, data provenance, and privacy-preserving computation; Critical Infrastructure and Cyber-Physical Security: Cyber resilience in physical and industrial systems, including IoT, satellites, and SCADA; Legal, Policy, and AI Governance in Digital Forensics: Studies bridging AI governance, digital law, compliance, and socio-technical policy; and Posters & Demos.