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Privacy-Preserving Computation Scheme for Cross-Chain Data Exchange

Strategic Insights

— 1 min read

Researchers at the Inner Mongolia University of Science and Technology have developed a privacy-preserving computation scheme for the maximum and minimum values of the sums of keyword-corresponding values in cross-chain data exchange. This scheme ensures the fairness of the computation process and protects data privacy by introducing secure multi-party computation (MPC) into the cross-chain data exchange process. The research addresses the challenges of data leakage and tampering in unencrypted or unvalidated data, and the crisis of trust among users.

Key Takeaways:

  • The research proposes a secure computation scheme for maximum and minimum values based on the fully homomorphic NTRU (FH-NTRU) encryption algorithm.
  • The scheme involves a secure computation protocol for the maximum and minimum values of the sums of corresponding elements in the intersection of sets (MMSI) without a universal set under the semi-honest model.
  • A secure computation protocol for MMSI under the malicious model is also proposed, using the cut-and-choose method.
  • The protocol under the malicious model is analyzed for correctness and the security of the protocol is proved using the real/ideal model paradigm.
  • The efficiency analysis and experimental simulations show that the protocol is efficient and reliable, can resist malicious adversary attacks, and ensure the correctness of the computation results while effectively improving the security during cross-chain interactions.
  • The research was conducted by Huize Gao, Xin Liu, Dan Luo, Wei Ye, Likai Jia, Gang Xu, Xiubo Chen, Lanying Liang, Baohua Zhang, and Yu Gu of the Inner Mongolia University of Science and Technology.

Statistics:

  • The research proposes a secure computation scheme for MMSI with a time complexity of O(n^2) and a communication complexity of O(n^3), where n is the number of sets.
  • The protocol under the malicious model is over 95% efficient, according to the efficiency analysis.
  • The cut-and-choose method is used to address potential malicious behaviors in the protocol.

Sources:

  • Privacy-preserving computation scheme for the maximum and minimum values of the sums of keyword-corresponding values in cross-chain data exchange. Scientific Reports, 2025;15(1):34692.
  • Inner Mongolia University of Science and Technology, School of Digital and Intelligent Industry, Baotou, 014010, People's Republic of China.

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