Experimental Evaluation of Secured Forensic Evidence Handling Scheme using Blockchain Technology

Modern criminal investigations rely on forensic evidence management, which necessitates careful handling, safe storage, and precise documenting of the chain of custody. Problems including data manipulation, illegal access, and a lack of transparency plague conventional evidence management systems. In response to these concerns, this study introduces a novel approach to forensic evidence management that makes use of blockchain technology. Nowadays, data plays a crucial role in every stage of the work process. Since data might change, it should be secure. In a diverse organization, we shall handle data capacity and portrayal. Data that is vital to a particular organization might be the target of an attack. As the prevalence of cybercrime rises, malicious actors are taking increasingly cunning actions to alter such data. Whatever the case may be, it is significantly impacting the expected scientific confirmation of provenance. Since forensic evidence moves through many stages during scientific examination, it is supposed to be preserved in this manner. With this approach, a report is created and then passes through various levels of delegation, such as a pathology lab, a forensic lab, the police, and so on. To create a clear framework with immutable measurable confirmations, blockchain technology innovation is the best choice. The efficiency of the proposed scheme is evaluated by cross-validation with the conventional security model called Secured Forensic Evidence Handler (SFEH). This paper introduced a novel algorithm called Heterogeneous Key Generation for Forensic Data Safety (HKGFDS) to maintain forensic details in a safer manner. By demonstrating how blockchain technology has the ability to revolutionize forensic evidence management methods, this research adds to what is already known. Improved and more trustworthy criminal investigations are possible outcomes of this new line of inquiry and its use in practical forensic contexts. But wider acceptance can’t happen unless scalability and interoperability issues are resolved.