Description
TL;DR: A cloud-storage integrity design that separates public and private data and uses a modified Merkle tree to reduce audit cost and computation time.
About This Document
Shruthi Gangadharaiah and Purohit Shrinivasacharya describe a protocol for predicting available cloud space and verifying stored data through third-party auditing. Their position-aware Merkle tree is intended to reduce client computation compared with public-key and bilinear-map approaches. The paper reports a simulation time of 0.00459 milliseconds for the proposed method; that is the authors' experimental result, not an independent performance guarantee.
Why Bitcoin People May Care
Merkle trees are central to Bitcoin, but this is not a Bitcoin paper. It applies a related integrity structure to cloud auditing and privacy. That makes it useful for seeing how the same tree concept changes when the problem is proving stored-data integrity rather than committing transactions into blocks.
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Document Details
- Title: Privacy-Preserving Cloud Storage with a Position-Aware Merkle Tree
- Author / organization: Shruthi Gangadharaiah and Purohit Shrinivasacharya
- Year: 2024
- Language: English
- Document type: Research paper
- Pages: 9
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