AI in Digital Forensics
Revolutionizing Digital Investigations with AI: Enhancing Accuracy, Speed, and Efficiency
Skills you will gain:
This workshop will delve into how AI is transforming digital forensics by improving the efficiency, accuracy, and speed of evidence collection and analysis. It will cover AI-powered tools like image classifiers, natural language processing (NLP), and automated evidence collection systems. Case studies and practical applications will demonstrate AI’s integration into cyber forensics and digital investigations.
Aim: To explore the role of AI in revolutionizing digital forensics, enhancing the analysis, collection, and interpretation of evidence for criminal investigations.
- Understand the intersection of AI, defect engineering, and 2D nanomaterials
- Learn how machine learning can optimize material properties for nanoelectronics
- Explore the applications of AI in quantum computing and next-gen electronic devices
What you will learn?
Day 1: Introduction to AI in Digital Forensics
- Overview of Digital Forensics & AI: Understand AI’s role in modernizing forensics, including key concepts and real-world applications.
- AI-Powered Forensic Tools: Explore tools like Magnet AXIOM for automated evidence collection, image analysis, and document processing.
- AI-Powered Forensic Tools: AI and ML enhance digital forensic investigations
- Hands-On Session: Introduction to using AI tools for image categorization and document analysis.
Day 2: Advanced AI Techniques and Applications
- AI Techniques for Evidence Analysis: Learn about NLP for text analysis, deep learning for image forensics, and AI in network forensics.
- Automating Forensic Workflows: Discuss AI’s role in automating tasks to reduce human error and speed up investigations.
- Hands-On Session: Use advanced AI features like anomaly detection and chat log analysis.
- Hands-On Session: Role of AI & ML in cyber-forensic evidence acquisition and analysis
Day 3: Legal, Ethical, and Practical Considerations
- Legal and Ethical Issues: Examine the legal implications, chain of custody, and ethical concerns in using AI for forensic investigations.
- Case Studies: AI flags fraud, traces malware, verifies identities—toward predictive, explainable forensics.
- Hands-On Session: Chain-of-custody, XAI, privacy/bias, human review; mitigate drift, adversarial attacks, Daubert/Frye.
Intended For :
- Materials scientists and engineers
- AI/ML engineers interested in material design
- Researchers in nanoelectronics and quantum computing
- Postgraduate students in nanotechnology and material science
Career Supporting Skills

