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SEVCOD: secure and efficient verifiable computation on outsourced data
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AI
DOI：10.1007/s10586-023-04190-9.png)
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Abstract
En 中文
Cloud computing has gained significant popularity, as a promising service platform in recent years. It facilitates the users to offload their resource-intensive computations to cloud server (CS) for efficient processing. Meanwhile, users prioritize the security and privacy of their sensitive data by encrypting it before outsourcing it to the CS. However, performing computations like multivariate polynomial function over encrypted data and verifying their correctness poses a major challenge. Homomorphic Encryption (HE) has been proposed as a solution to enable computations over encrypted data while maintaining data confidentiality. This work proposes a secure and efficient scheme for verifiable computation on outsourced data, named SEVCOD. SEVCOD combines the power of multivariate polynomial factorization and homomorphic encryption to enable public verification of CS's computation results preserving confidentiality of both data and result. The effectiveness of our scheme is validated through security proofs and performance analysis. The result analysis demonstrates that, SEVCOD significantly reduces computational burden for verifiers and enhances the overall efficiency of the outsourced computation process.
Keywords:
Outsourced data
Outsourced computation
Verifiable computing
Encrypted data
Polynomial factorization
Journal
C
IF:
4.1
Papers:
5.0K
Citations:
7.5K