Cybercrime and Computer Forensics in Epoch of Artificial Intelligence in India

AI creates a "dual-use" problem in criminal investigations: The paper finds that artificial intelligence functions simultaneously as both a tool for crime (enabling deepfakes and anti-forensics attacks) and a tool for solving crime (automating evidence extraction). This tension requires careful regulation to prevent misuse while preserving investigative capabilities.

India's privacy law may conflict with forensic needs: The Digital Personal Data Protection Act, 2023 emphasizes data minimization, but criminal investigations often require retaining large amounts of data. The paper identifies this as a "critical tension" that Indian law has not yet adequately resolved.

AI forensic tools have significant blind spots: While machine learning can recognize patterns with high accuracy, the research warns that these systems are vulnerable to "data poisoning" (corrupted training data) and algorithmic bias, meaning AI-generated evidence could be unreliable or discriminatory if not carefully validated.

Current laws don't address AI-specific crimes: Existing legal definitions inadequately cover crimes committed by AI systems or crimes where AI is the target. The paper calls for updated legal frameworks that specifically address these "tool crimes" and "target crimes."

Explainable AI should be required for criminal evidence: The paper proposes a "human-centric" forensic model requiring explainable AI (XAI)—meaning investigators and courts must be able to understand why an AI system reached its conclusions—to ensure evidence is admissible and trustworthy in court.