Design of an Improved Model for Forensic Chain-of-Custody Using ZK-TIV, MV-PGChain, and AWReS

Abstract

The digital forensic investigation process overwhelmingly depends on the unbroken, tamper-proof, and audit able Chain of Custody for evidence data. However, most traditional Chain of Custody systems suffer limitations being either static permission control, weak traceability, or even worse lack implementation of cryptographically enforced privacy and integrity guarantees in evidence lifecycle management. These failures can disable real-time, transparent, and secure evidence life cycle management, especially in costly, heterogeneous, and multi-party environments. The work introduces FAIR-CoC, a Forensic Adaptive Integrity and Reputation Chain-of-Custody system conceptually based on the Hybrid Blockchain-IPFS CoC Ledger (HBI-CoC) architecture to resolve these problems. This system uses IPFS as a decentralized repository for forensic artifacts while using private Ethereum blockchain for immutable record keeping of cryptographic hashes, access metadata, and smart contract logic. Furthermore, the framework consists of five key parts, ZK-TIV (Zero-Knowledge Temporal Integrity Verifier) enables evidence access within permissible timestamp windows using zk-SNARK proofs without revealing accessor identities to enhance privacy and temporal accountability in the process; the MV-PGChain (MultiVector Provenance Graph Chain) builds high fidelity provenance graph capturing handler, location, tool, and timestamp changes, with Merkle root snap-shots anchored on-chains; AWReS (Access Weighted Reputation Scorer) dynamically assesses trustworthiness for custodians using on-chain behavioral analytics; HAT-FSS (Homomorphic Audit Tags for Forensic Shard Storage) allows encrypted auditability for IPFS-stored shards using homomorphic verification tags; PA-ESC (Predictive Access Escalation Smart Contracts) embeds AI-based access behavior modeling to automate privilege revocation or escalations. Collectively, these functionalities present a novel adaptive and privacy-preserving CoC framework with solid integrity, traceability, and trust guarantees. Experimental evaluations contend with low latency and accuracy whether across all modules, establishing FAIR-CoC as a leap forward toward secure, scalable, and intelligent forensic chain-ofcustody systems.