AI-Enabled Digital Evidence Validation and Predictive Cyber Forensics Across Multi-Cloud Enterprise Systems
DOI:
https://doi.org/10.66592/6x6srv97Keywords:
AI-enabled digital forensics, digital evidence validation, predictive cyber forensics, multi-cloud security, machine learning, evidence integrity, behavioral analytics, threat intelligence, chain of custody, explainable artificial intelligence.Abstract
The rapid adoption of multi-cloud enterprise systems has significantly increased the complexity of cybersecurity investigations, digital evidence management, and incident response. Distributed applications, interconnected infrastructure, and diverse cloud storage environments generate enormous volumes of security-related data that require accurate validation and timely forensic analysis. Traditional digital forensic approaches often face limitations in maintaining evidence integrity, identifying sophisticated attack patterns, and correlating security events across heterogeneous cloud platforms. This research proposes an AI-enabled digital evidence validation and predictive cyber forensics framework designed to improve the reliability, accuracy, and efficiency of enterprise cybersecurity investigations. The proposed framework integrates machine learning, behavioral analytics, cryptographic hashing, automated evidence correlation, and predictive threat intelligence to identify suspicious activities and validate digital artifacts across multi-cloud environments. The methodology incorporates evidence acquisition, integrity verification, forensic metadata analysis, anomaly detection, attack sequence reconstruction, and risk prediction. Explainable artificial intelligence techniques provide transparent investigation insights, while distributed evidence management mechanisms support traceability and secure preservation. The framework also emphasizes chain-of-custody management, access governance, and forensic reproducibility to strengthen the credibility of investigation outcomes. By combining predictive analytics with automated digital evidence validation, the proposed approach aims to reduce investigation time, improve threat identification, and support proactive cyber defense. The research establishes an intelligent foundation for scalable, trustworthy, and adaptive digital forensics across modern enterprise cloud infrastructures.References
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