An Intelligent Semi-Honest System for Secret Matching against Malicious Adversaries

Author:

Liu Xin12,Kong Jianwei1,Luo Dan3,Xiong Neal4ORCID,Xu Gang5,Chen Xiubo6

Affiliation:

1. School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou 014010, China

2. School of Computer Science, Shaanxi Normal University, Xi’an 710062, China

3. Computer Department, Tianjin Ren’ai College, Tianjin 301636, China

4. Department of Computer, Mathematical and Physical Sciences, Sul Ross State University, Alpine, TX 79830, USA

5. School of Information Science and Technology, North China University of Technology, Beijing 100144, China

6. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China

Abstract

With natural language processing as an important research direction in deep learning, the problems of text similarity calculation, natural language inference, question and answer systems, and information retrieval can be regarded as text matching applications for different data and scenarios. Secure matching computation of text string patterns can solve the privacy protection problem in the fields of biological sequence analysis, keyword search, and database query. In this paper, we propose an Intelligent Semi-Honest System (ISHS) for secret matching against malicious adversaries. Firstly, a secure computation protocol based on the semi-honest model is designed for the secret matching of text strings, which adopts a new digital encoding method and an ECC encryption algorithm and can provide a solution for honest participants. The text string matching protocol under the malicious model which uses the cut-and-choose method and zero-knowledge proof is designed for resisting malicious behaviors that may be committed by malicious participants in the semi-honest protocol. The correctness and security of the protocol are analyzed, which is more efficient and has practical value compared with the existing algorithms. The secure text matching has important engineering applications.

Funder

National Natural Science Foundation of China: Big Data Analysis based on Software Defined Networking Architecture

NSFC

Inner Mongolia Natural Science Foundation

2023 Inner Mongolia Young Science and Technology Talents Support Project

2022 Fund Project of Central Government Guiding Local Science and Technology Development

2022 Basic Scientific Research Project of Direct Universities of Inner Mongolia

2022 “Western Light” Talent Training Program “Western Young Scholars” Project

14th Five-Year Plan of Education and Science of Inner Mongolia

2023 Open Project of the State Key Laboratory of Network and Exchange Technology

2022 Inner Mongolia Postgraduate Education and Teaching Reform Project

the 2022 Ministry of Education Central and Western China Young Backbone Teachers and Domestic Visiting Scholars Program

Inner Mongolia Discipline Inspection and Supervision Big Data Laboratory Open Project Fund

Baotou Kundulun District Science and Technology Plan Project

Inner Mongolia Science and Technology Major Project

Fundamental Research Funds for Beijing Municipal Commission of Education

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

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