Cybercrime and Computer Forensics in Epoch of Artificial Intelligence in India

TL;DR

This paper examines the challenges and legal implications of integrating AI into digital forensics in India, focusing on privacy, adversarial threats, and the need for explainable AI to ensure evidence integrity.

Contribution

It provides a doctrinal analysis of Indian privacy laws in relation to AI-driven cybercrime and proposes a human-centric, explainable AI forensic model to address legal and technical gaps.

Findings

Machine Learning achieves high pattern recognition accuracy but faces data poisoning risks.

Legal definitions currently do not adequately cover AI-driven crimes.

Synchronizing privacy laws with international standards is essential for effective digital forensics.

Abstract

The integration of generative Artificial Intelligence into the digital ecosystem necessitates a critical re-evaluation of Indian criminal jurisprudence regarding computational forensics integrity. While algorithmic efficiency enhances evidence extraction, a research gap exists regarding the Digital Personal Data Protection Act, 2023's compatibility with adversarial AI threats, specifically anti-forensics and deepfakes. This study scrutinizes the AI "dual-use" dilemma, functioning as both a cyber-threat vector and forensic automation mechanism, to delineate privacy boundaries in high-stakes investigations. Employing a doctrinal legal methodology, the research synthesizes statutory analysis of the DPDP Act with global ethical frameworks (IEEE, EU) to evaluate regulatory efficacy. Preliminary results indicate that while Machine Learning offers high accuracy in pattern recognition, it introduces vulnerabilities regarding data poisoning and algorithmic bias. Findings highlight a critical tension between the Act's data minimization principles and forensic data retention requirements. Furthermore, the paper identifies that existing legal definitions inadequately encompass AI-driven "tool crimes" and "target crimes." Consequently, the research proposes a "human-centric" forensic model prioritizing explainable AI (XAI) to ensure evidence admissibility. These implications suggest that synchronizing Indian privacy statutes with international forensic standards is imperative to mitigate synthetic media risks, establishing a roadmap for future legislative amendments and technical standardization.