Comprehensive Systematic Review and Critical Evaluation of AI-Driven Cybercrime Detection, eFIR Systems, and Legal Frameworks in Indian Policing

Abstract

As cyber-threats become increasingly sophisticated in the artificial intelligence (AI) era, law enforcement agencies face severe operational bottlenecks in reporting, triaging, and processing cybercrime complaints [1]. Current literature spans machine learning detection architectures, e-FIR lodging portals, legal framework analyses, and police administrative studies [2, 9]. However, existing research remains highly fragmented: technical threat-detection systems operate in isolation from legal work-flows, while policy and legal studies lack actionable automated implementations [7, 17]. This paper conducts a comprehensive critical evaluation of 20 seminal and contemporary works cover-ing AI cybercrime models, blockchain e-FIR platforms, statutory provisions (IT Act, BNS, DPDP Act), and police operational reports [1–20]. By systematically identifying methodological limi-tations, variables, and procedural gaps across existing studies, we establish the explicit necessity for an integrated, AI-driven Smart FIR system capable of automated complaint triage, evidence extraction, legal mapping, and transparent police workflow integration.