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Related Experiment Videos

TRUST: A toolkit for TEE-assisted secure outsourced computation over integers.

Bowen Zhao1,2, Jiuhui Li1, Cheng Qiao3

  • 1Guangzhou Institute of Technology, Xidian University, Guangzhou 510555, China.

Fundamental Research
|June 11, 2026
PubMed
Summary
This summary is machine-generated.

We introduce TRUST, a toolkit for secure outsourced computation (SOC) using Trusted Execution Environments (TEEs) and homomorphic encryption. TRUST enhances computational efficiency and security for encrypted data processing, enabling new applications like secure data trading.

Keywords:
Data tradingHomomorphic encryptionPrivacy protectionSecure computingTEE

Related Experiment Videos

Area of Science:

  • Computer Science
  • Cryptography
  • Cloud Computing

Background:

  • Secure Outsourced Computation (SOC) leverages cloud computing and privacy-enhancing technologies like homomorphic encryption.
  • Existing SOC solutions often struggle with computational efficiency and adaptability for complex operations on encrypted data.
  • Expanding SOC capabilities for diverse use cases remains a critical research challenge.

Purpose of the Study:

  • To propose TRUST, a novel toolkit for Trusted Execution Environment (TEE)-assisted SOC over integers.
  • To enhance the efficiency and adaptability of SOC by integrating Rich Execution Environment (REE) and TEE computations.
  • To develop secure protocols for unary, binary, and ternary operations and demonstrate a secure data trading application (SEAT).

Main Methods:

  • Designed a system architecture integrating REE and TEE computations within a single TEE-equipped cloud server.
  • Introduced a (2, 2)-threshold homomorphic cryptosystem to facilitate hybrid computation between REE and TEE.
  • Developed a suite of SOC protocols for various operations and a secure data trading application (SEAT) based on TRUST.

Main Results:

  • TRUST enables efficient and secure SOC, preventing collusion attacks and mitigating TEE-related secret leakage risks.
  • Experimental evaluations show TRUST outperforms state-of-the-art methods, requiring no data alignment or network communication.
  • The SEAT application demonstrates effectiveness comparable to baseline methods without data protection.

Conclusions:

  • TRUST provides a robust and efficient toolkit for TEE-assisted SOC, addressing limitations of previous solutions.
  • The integration of REE and TEE with a novel homomorphic cryptosystem enhances security and computational capabilities.
  • TRUST and SEAT pave the way for more secure and versatile applications in cloud computing and data privacy.