PRISM: Provable and Immutable Storage Mechanism with Ethereum-based PDP

Highlights • Identifying threats that cannot be countered by theoretical security based on STRIDE threat analysis of an existing provable data possession (PDP) system • Designing a PDP system with practical security features to counter threats that cannot be addressed with theoretical security alone • Presenting the implementation of the proposed PDP system, PRISM, which is also provided as an open-source software • Validating security properties through property-based fuzz testing with 10,000 randomized test runs per security property • Demonstrating PRISM’s key strengths through comprehensive experiments, including basic performance, trade-offs between processing time and data auditing efficiency, and capabilities for detecting data anomalies Digital platforms are increasingly recognized as a cornerstone for advanced virtual spaces such as smart cities and the metaverse, where vast amounts of data are aggregated, analyzed, and utilized to make critical decisions. These platforms rely on data fusion to integrate diverse sources of information, encompassing individual behavior, urban dynamics, and system states. Through auditing against data tampering, loss, and substitution, enabling the detection of such threats is critical to building a highly reliable system. This paper introduces PRISM (Provable and Immutable Storage Mechanism), an Ethereum-based Provable Data Possession (PDP) system designed to integrate data reliability and security with decentralized auditing. PDP, a cryptographic protocol that enables data integrity in untrusted cloud storage, has seen extensive research focusing on theoretical security and computational efficiency. PRISM extends this foundation by addressing practical security concerns, including the integration of authentication and authorization, data immutability, data uniqueness, data freshness, and state management, to ensure a robust system implementation. Experiments on processing costs and parameter analysis reveal a trade-off between the costs and detection accuracy and demonstrate that PRISM provides efficient data auditing.