Digital forensics plays a vital role in modern cybersecurity by enabling the identification, preservation, analysis, and presentation of digital evidence following cyber incidents. As cyberattacks continue to grow in scale, sophistication, and complexity, traditional forensic techniques face significant challenges in processing massive volumes of heterogeneous data generated by cloud platforms, Internet of Things (IoT) devices, mobile systems, social media, blockchain networks, and Artificial Intelligence (AI)-enabled applications. AI technologies—including machine learning, deep learning, natural language processing (NLP), computer vision, and Large Language Models (LLMs)—are transforming digital forensic investigations by automating evidence collection, accelerating malware and log analysis, detecting anomalies, reconstructing attack timelines, and supporting intelligent decision-making. At the same time, AI introduces new forensic challenges, such as investigating AI-generated content, deepfakes, autonomous AI agents, and attacks targeting AI systems.

The International Conference on Cyber Security in Artificial Intelligence (ICCSAI 2027) invites original research contributions on Digital Forensics and AI. This track provides an interdisciplinary platform for researchers, forensic investigators, cybersecurity professionals, AI scientists, law enforcement agencies, legal experts, and industry practitioners to present innovative research on AI-enhanced digital forensics and forensic readiness. Contributions addressing intelligent forensic analysis, AI-assisted evidence management, cloud and IoT forensics, blockchain forensics, explainable AI, privacy-preserving forensic techniques, and legal and ethical considerations are particularly encouraged.

1. AI-Driven Digital Forensics

• AI-Assisted Digital Forensics

• Machine Learning for Digital Investigations

• Deep Learning for Digital Forensics

• Large Language Models (LLMs) for Forensic Analysis

• Generative AI for Forensic Automation

• Intelligent Evidence Analysis

2. Digital Evidence Acquisition and Analysis

• Digital Evidence Collection and Preservation

• Digital Evidence Integrity Verification

• Automated Evidence Processing

• File System and Disk Forensics

• Memory (RAM) Forensics

• Live System Forensics

• Timeline Reconstruction and Event Correlation

3. Network and Cloud Forensics

• Network Traffic Forensics

• Cloud Forensics

• Multi-Cloud and Hybrid Cloud Forensics

• Container and Kubernetes Forensics

• Virtual Machine Forensics

• Software-as-a-Service (SaaS) Forensics

• Serverless Environment Forensics

4. Malware and Incident Forensics

• AI-Based Malware Analysis

• Malware Reverse Engineering

• Ransomware Forensics

• Advanced Persistent Threat (APT) Investigation

• Incident Response and Forensic Investigation

• Threat Attribution Using AI

• AI-Assisted Root Cause Analysis

5. Mobile, IoT, and Edge Forensics

• Mobile Device Forensics

• Internet of Things (IoT) Forensics

• Industrial IoT (IIoT) Forensics

• Edge Computing Forensics

• Wearable Device Forensics

• Vehicle and Autonomous System Forensics

• Smart Home and Smart City Forensics

6. Multimedia and AI Content Forensics

• Deepfake Detection and Analysis

• Image and Video Forensics

• Audio Forensics

• Synthetic Media Analysis

• Generative AI Content Forensics

• AI-Generated Document Verification

7. Blockchain and Cryptocurrency Forensics

• Blockchain Forensics

• Cryptocurrency Transaction Analysis

• Smart Contract Forensics

• Web3 and Decentralized Application (DApp) Forensics

• NFT Fraud Investigation

• Digital Asset Recovery

8. Anti-Forensics and Countermeasures

• Anti-Forensic Techniques

• Detection of Evidence Tampering

• Obfuscation and Steganography Detection

• Secure Chain of Custody

• Evidence Authentication

• Digital Evidence Validation

9. AI for Threat Intelligence and Investigation

• AI-Based Cyber Threat Intelligence

• Automated Threat Hunting

• AI for Security Information and Event Management (SIEM)

• AI for Security Orchestration, Automation, and Response (SOAR)

• User and Entity Behavior Analytics (UEBA)

• Explainable AI for Threat Attribution

10. Privacy, Ethics, and Legal Issues

• Privacy-Preserving Digital Forensics

• Digital Forensic Readiness

• Legal and Ethical Challenges in AI-Based Forensics

• Regulatory Compliance for Digital Evidence

• Explainable AI for Digital Investigations

• AI Governance in Forensic Systems

11. Emerging Technologies

• Quantum Digital Forensics

• Federated Learning for Forensics

• Autonomous AI for Digital Investigations

• Digital Twins for Forensic Analysis

• Cyber-Physical Systems (CPS) Forensics

• Explainable AI for Forensic Decision Support

12. Evaluation, Benchmarking, and Applications

• Digital Forensic Frameworks and Tools

• AI Benchmarking for Digital Forensics

• Digital Forensic Datasets

• Performance Evaluation of AI-Based Forensic Models

• Industrial Case Studies

• Law Enforcement Applications

• Best Practices in AI-Enabled Digital Forensics