Cloud Data Retrievability Proof via Auditing Intermediary
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Solution Overview
Problem
Conventional methods for proving retrievability of data in cloud storage rely on users to regularly verify data integrity, which is burdensome and costly, and do not effectively protect against malicious cloud providers or auditors.
Innovation Solution
A method and system that involves exchanging credentials between user, storing, and auditing devices for secure communication, encoding information, verifying correctness using unpredictable random information, and validating correctness information to prove retrievability, leveraging Bitcoin for pseudo-randomness and secure log files to ensure data integrity and accountability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users regularly verify data integrity themselves, then data security is improved, but user burden and computational overhead increase
Solution Approach 1:
The patent introduces an auditing device as an intermediary between the user device and storing device. The auditing device performs verification operations on behalf of the user, reducing the user's direct involvement and computational burden while maintaining data security. The user device only needs to exchange credentials and validate correctness information, not perform full verification itself.
Solution Approach 2:
The verification process is segmented into distinct roles: the user device generates credentials and validates results, the auditing device performs verification operations, and the storing device stores data. This segmentation allows the computationally intensive verification to be performed by specialized auditing devices rather than requiring users to handle all verification tasks themselves.
2Reliability
If users perform verification operations, then data integrity is ensured, but computational overhead and costs increase
Solution Approach 1:
The auditing device serves as an intermediary that performs computationally intensive verification operations, freeing the user device from heavy computational tasks. The user device only performs lightweight operations such as credential exchange and validation of correctness information, significantly reducing computational overhead and energy consumption.
Solution Approach 2:
Instead of requiring users to perform complete verification of all stored data, the system uses selective verification where the auditing device performs verification operations on samples or specific portions of data. This partial verification approach maintains data integrity assurance while reducing the overall computational burden compared to exhaustive verification.
3Reliability
If cloud providers are trusted to deploy security mechanisms, then data security is improved, but costs are transferred to providers and trust is required
Solution Approach 1:
The auditing device acts as an independent intermediary that verifies data integrity without requiring users to trust cloud providers directly. The auditing device provides objective verification and generates correctness information that users can validate, creating a trustless verification mechanism where users rely on cryptographic proofs rather than trust in service providers.
Solution Approach 2:
The system implements a feedback mechanism where the auditing device continuously monitors data integrity and provides correctness information back to the user device. This feedback loop enables users to verify data security status without directly managing security mechanisms, reducing the complexity of the trust model while maintaining strong security guarantees.
Data Source
AI summary
A method, performed by a user device, for proving retrievability (POR) of information includes: a1) exchanging credentials with a storing device and an auditing device to be used for communication between them; b1) encoding the information to be stored on the storing device; c1) initiating storing the encoded information on the storing device; d1) receiving correctness information, wherein the correctness information is secure and is generated based on the result of verification using unpredictable random information; and e1) validating the correctness information and unpredictable random information for proving retrievability of the stored information.