A Secure Multi-Party Computation Protocol for Graph Editing Distance against Malicious Attacks

Author:

Liu Xin12,Kong Jianwei1,Peng Lu3,Luo Dan4,Xu Gang5,Chen Xiubo2,Liu Xiaomeng1

Affiliation:

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

2. State Key Laboratory of Network and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China

3. Beijing Institute of Computer Technology and Applications, Beijing 100039, China

4. Department of Computer Science, Tianjin Renai University, Tianjin 301636, China

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

Abstract

The secure computation of the graph structure is an important element in the field of secure calculation of graphs, which is important in querying data in graphs, since there are no algorithms for the graph edit distance problem that can resist attacks by malicious adversaries. In this paper, for the problem of secure computation of similarity edit distance of graphs, firstly, the encoding method applicable to the Paillier encryption algorithm is proposed, and the XOR operation scheme is proposed according to the Paillier homomorphic encryption algorithm. Then, the security algorithm under the semi-honest model is designed, which adopts the new encoding method and the XOR operation scheme. Finally, for the malicious behaviors that may be implemented by malicious participants in the semi-honest algorithm, using the hash function, a algorithm for secure computation of graph editing distance under the malicious model is designed, and the security of the algorithm is proved, and the computational complexity and the communication complexity of the algorithm are analyzed, which is more efficient compared with the existing schemes, and has practical value. The algorithm designed in this paper fills the research gap in the existing literature on the problem of graph edit distance and contributes to solving the problem.

Funder

National Natural Science Foundation of China

Inner Mongolia Natural Science Foundation

2023 Inner Mongolia Young Science and Technology Talents Support Project

2022 Basic Scientific Research Project of Direct Universities of Inner Mongolia

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

2022 Chinese Academy of Sciences “Western Light” Talent Training Program “Western Young Scholars” Project

Open Foundation of State key Laboratory of Networking and Switching Technology

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

Baotou Kundulun District Science and Technology Plan Project

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

Inner Mongolia Science and Technology Major Project

2022 Inner Mongolia Postgraduate Education and Teaching Reform Project

Inner Mongolia Postgraduate Scientific Research Innovation Project

Research and Application Project of Big Data Privacy Security Computing System

Publisher

MDPI AG

Subject

General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Securing Web Data and Privacy in AIoT Systems;Advances in Web Technologies and Engineering;2024-05-16

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