Generative AI in Forensic Data Analysis: Opportunities and Ethical Implications for Cloud-Based Investigations

Abstract

Generative Artificial Intelligence (AI) has emerged as a powerful tool in forensic data analysis, particularly in cloud-based investigations. By leveraging its ability to simulate, predict, and reconstruct, generative AI offers transformative potential in automating complex forensic tasks, such as filling gaps in incomplete data, modelling cyberattack scenarios, and creating predictive analytics for future threat detection. This paper examines the integration of generative AI within forensic investigations, showcasing how its advanced capabilities can enhance the accuracy and efficiency of cloud-based forensic processes. However, alongside these opportunities, generative AI introduces significant ethical concerns that must be addressed. The potential misuse of generative AI in fabricating data or producing biased analyses poses risks to the integrity of forensic investigations, which can lead to compromised evidence and misleading outcomes. Moreover, issues surrounding privacy, consent, and the ethical use of personal data are particularly pressing in the cloud computing environment, where forensic analysis often involves large-scale datasets. This paper explores the ethical challenges that arise when integrating generative AI into forensics and offers a framework for its responsible and ethical use. Key considerations include implementing bias mitigation strategies, ensuring transparent data usage, and maintaining strict regulatory compliance. By balancing the opportunities with the ethical implications, this study aims to provide a comprehensive roadmap for the adoption of generative AI in forensic investigations, ensuring its benefits are realized while minimizing potential harm.