Merkle-Tree-Based Verifiable Public Data Auditing for Cloud Object Storage Using Smart Contracts
Siri Reddy Tadi, K. Gangadhara Rao, M. Venu Gopalachari, C. Chetann Reddy, Jaswanth Bhimireddy
Owners of data in cloud object storage cannot directly check whether the provider still keeps every object unchanged. Existing research mostly checks blocks inside files or relies on third-party auditors, and less attention has been given to checking each object against a public blockchain reference while measuring the cost. A full-data audit downloads every object and compares it with a saved hash list, which is slow and only as reliable as that list. We propose a public auditing system in which the SHA-256 hash of each object and its name forms a leaf of a Merkle tree, so the whole dataset is represented by one Merkle root. This root is stored in an Ethereum smart contract as a trusted public record, while the objects stay with the provider. An auditor downloads an object, rebuilds the root using a short Merkle proof and compares it with the stored root, marking the object as intact, modified or missing. In five experiments on an S3-compatible store and a local Hardhat blockchain (normal audit, single- and multiple-object tampering, deletion and scalability), the system detected 15 of 15 single modifications, 2,205 of 2,205 modified objects and 830 of 830 deleted objects with no false alarms. The proof needed only 14 hashes for 10,000 objects, so checking one object took about 10 ms and a 100-object sample about 150 ms regardless of dataset size, while a full audit of 10,000 objects (14.3 s) took about as long as downloading them (13.5 s). Storing the root cost 91,863 gas, 252 times less than storing 1,000 hashes on-chain. The system thus shows exactly which objects were modified or are missing, with its main savings coming from checking selected objects.
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