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An efficient polynomial-based verifiable computation scheme on multi-source outsourced data.

Yiran Zhang1, Huizheng Geng2, Li Su1

  • 1China Mobile Research Institute, Beijing, 100053, China.

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|April 12, 2024
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Summary
This summary is machine-generated.

This study introduces an efficient verifiable computation scheme for multi-source outsourced data. It enhances polynomial verification speed using Horner's method, improving efficiency for cloud computing tasks.

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Area of Science:

  • Cloud Computing Security
  • Cryptography
  • Distributed Systems

Background:

  • Cloud computing enables outsourcing complex tasks, but untrusted servers pose risks of data leakage and incorrect results.
  • Verifiable computation is crucial for ensuring result integrity without compromising user privacy.
  • Existing polynomial-based verifiable computation schemes often struggle with multi-source data and efficiency.

Purpose of the Study:

  • To propose an efficient polynomial-based verifiable computation scheme for multi-source outsourced data.
  • To address the limitations of existing schemes regarding data source diversity and computational efficiency.
  • To enhance the security and privacy of outsourced computations in cloud environments.

Main Methods:

  • Optimization of polynomial representation using Horner's method for faster verification.
  • Design of a novel homomorphic verification tag to support multi-source data inputs.
  • Mathematical proofs for scheme correctness and rationality.
  • Numerical analysis and experimental evaluation of efficiency.

Main Results:

  • The proposed scheme efficiently handles polynomial computations with inputs from multiple data sources.
  • Optimization using Horner's method significantly increases verification speed.
  • Experimental results show data contributors can sign 1000 data points in 2 seconds.
  • Verification of a 100-power polynomial function takes only 18 milliseconds.

Conclusions:

  • The developed scheme offers a significant improvement in efficiency compared to existing methods for verifiable multi-source outsourced polynomial computation.
  • The approach enhances the practicality of secure and verifiable computations in cloud environments.
  • This work contributes to more robust and efficient data outsourcing solutions.