Artificial Intelligence AI-Driven Digital Forensics in Cybercrime Investigations: Addressing Data Privacy and Ethical Considerations

Abstract

Cybercrime is growing at a rapid pace and it has proved that traditional digital forensic investigation approaches lack a number of critical gaps that demand the use of Artificial Intelligence (AI) to improve the efficiency, accuracy and scalability of digital investigations. The introduction of AI in forensic domains comes with concurrent challenges to issues like data privacy and confidentiality, algorithmic bias, AI ethical accountability, and legal admissibility for evidence and testimony. In this paper, the authors present the AI-Driven Ethical Forensic Investigation Framework (ADEFIF). The modular architecture is novel; includes a combination of machine learning (ML), deep learning (DL), natural language processing (NLP), explainable AI (XAI), federated learning, differential privacy, and blockchain-based audit logging as part of a digital forensic investigation system. The ADEFIF is based on four theoretic pillars: Socio-Technical Systems Theory (STST), Deontological Ethics, Data Protection and Privacy Theory, and the Explainable AI Framework (ExAI). The framework demonstrates excellent AI accuracy across all of the public, synthetic, and simulated forensic datasets, with a value of 94.5%, excellent ethical compliance score of 92.0%, and a privacy protection score value of 93.0%, resulting in an overall system performance of 93.2% across 95,000 records across the three datasets. Comparative benchmarking proves that ADEFIF surpasses all current frameworks such as Traditional Digital Forensics, Multidimensional AI Forensic Analysis Framework (MAFAF), and Privacy-by-Design AI Forensic Model (PbDAIF), in all the assessment dimensions. By incorporating investigative strategies alongside ethical considerations, privacy protections, and protocols, this framework fills a crucial space in this research niche, both by addressing the need for responsible and legally robust systems of cybercrime investigations and by serving as a blueprint for continuous refinement and innovation within AI-powered investigative frameworks.