Industry 4.0 crime scene investigation: A review and zero-trust digital forensic architecture for evidence integrity

Industry 4.0 technology adoptions in crime scene investigation has led to the emergence of a distributed forensic ecosystem involving IoT devices, AI-driven forensic analytics, cloud systems, blockchain platforms, digital twin-based forensics, robotics, and immersive environments for forensic examination. Although these technologies can enhance forensic automation and evidence correlation, there are critical information security and digital forensic issues that come with their deployment, which include evidence tampering, volatility of evidence, adversarial use of AI, insecurity in IoT communication channels, weaknesses in authentication methods, exposure to privacy violations, and threats to the chain of custody. Studies conducted on such technologies tend to treat them separately and overlook frameworks that ensure evidence trustworthiness, privacy preservation, and legal investigations. This study seeks to fill this research gap by analyzing Industry 4.0 technologies in terms of evidence life cycle management. Building upon the identified gaps in existing forensic frameworks, this study proposes a conceptual Zero-Trust Digital Forensic Architecture (ZTF-CSI) that unifies secure evidence acquisition, continuous identity verification, blockchain-enabled chain-of-custody, cryptographic integrity validation, explainable AI-assisted evidence verification, and privacy-preserving cloud forensics into a single evidence lifecycle model. Unlike prior studies that address these technologies independently, the proposed architecture integrates them within a security-by-design framework intended to preserve evidence integrity, strengthen forensic trustworthiness, and improve legal defensibility throughout Industry 4.0 crime scene investigations. The Zero Trust Digital Forensics Framework (ZTF-CSI) is a conceptual framework architecture based on the systematic analysis of the literature review findings and will serve as the basis for a future prototype and experimental validation.