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Multi-party Secure Comparison of Strings Based on Outsourced Computation

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Machine Learning for Cyber Security (ML4CS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13656))

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Abstract

Data is an important production factor in the era of digital economy. Privacy computing can ensure that data providers do not disclose sensitive data, carry out multi-party joint analysis and computation, securely and privately complete the full excavation of data value in the process of circulation, sharing, fusion, and calculation, which has become a popular research topic. String comparison is one of the common operations in data processing. To address the string comparison problem in multi-party scenarios, we propose an algorithm for secure string comparison based on outsourced computation. The algorithm encodes the strings with one hot encoding scheme and encrypts the encoded strings using an XOR homomorphic encryption scheme. The proposed algorithm achieves efficient and secure string comparison and counts the number of different characters with the help of a cloud-assisted server. The proposed scheme is implemented and verified using the new coronavirus gene sequence as the comparison string, and the performance is compared with that of a state-of-the-art security framework. Experiments show that the proposed algorithm can effectively improve the string comparison speed and obtain correct comparison results without compromising data privacy.

Supported by the Scientific and Technological Project of State Grid Jiangsu Electric Power Co., Ltd (No. J2021038).

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Authors and Affiliations

  1. State Grid Jiangsu Marketing Service Center, State Grid Jiangsu Electric Power Co. Ltd., Nanjing, China

    Xin Zhang, Chao Shan & Yunfeng Zou

Authors
  1. Xin Zhang
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  2. Chao Shan
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  3. Yunfeng Zou
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Corresponding author

Correspondence to Xin Zhang .

Editor information

Editors and Affiliations

  1. School of Computing and Informatics, University of Louisiana at Lafayette, Lafayette, IN, USA

    Yuan Xu

  2. Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, China

    Hongyang Yan

  3. Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, China

    Huang Teng

  4. Guangdong Polytechnic Normal University, Guangzhou, China

    Jun Cai

  5. Institute of Artificial Intelligence and Blockchain, Guangzhou University, Guangzhou, China

    Jin Li

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Zhang, X., Shan, C., Zou, Y. (2023). Multi-party Secure Comparison of Strings Based on Outsourced Computation. In: Xu, Y., Yan, H., Teng, H., Cai, J., Li, J. (eds) Machine Learning for Cyber Security. ML4CS 2022. Lecture Notes in Computer Science, vol 13656. Springer, Cham. https://doi.org/10.1007/978-3-031-20099-1_2

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  • DOI: https://doi.org/10.1007/978-3-031-20099-1_2

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