BLOCKCHAIN-ENABLED EVIDENCE INTEGRITY AND TRANSPARENCY FRAMEWORK FOR LAW ENFORCEMENT AGENCIES
DOI:
https://doi.org/10.64751/ajaccm.2026.v6.n2.pp571-581Keywords:
Hash-based Verification, Modern Law Enforcement Systems, Audit Logging, Decentralized Architecture, Judicial Data Security.Abstract
The growing dependence on digital technologies in criminal investigations has significantly increased the importance of secure and reliable digital evidence management. Digital evidence, including images, case records, and metadata (data that describes other data), plays a vital role in establishing facts and supporting judicial decisions. However, ensuring the integrity, authenticity, and traceability of such evidence remains a major challenge in modern law enforcement environments. Traditional systems for managing digital evidence are primarily based on centralized architectures, where data is stored and controlled by a single authority. Although these systems provide basic security features such as access control and encryption, they are vulnerable to risks including unauthorized modification, data tampering, single points of failure, and lack of transparency. Furthermore, existing systems often lack effective mechanisms for maintaining a verifiable chain of custody (coc) and detecting alterations in stored evidence, which can compromise the credibility of investigations. These limitations highlight the need for a more secure, transparent, and tamper-resistant solution that ensures trust in digital evidence throughout its lifecycle. To address this, the proposed system introduces a blockchain-based evidence management framework integrated with cryptographic hashing techniques using secure hash algorithm 256-bit (sha-256). The system securely records evidence metadata on a decentralized ledger while storing associated files with hash-based integrity verification. It also incorporates role-based access control (rbac – role-based access control) for administrators, officers, and auditors, along with a coc logging mechanism to track all interactions with the evidence.
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