兵工自动化2025，Vol.44Issue(6)：48-51,81,5.DOI:10.7690/bgzdh.2025.06.011
基于分布式机器学习算法的科研审计系统安全漏洞识别方法
Security Vulnerability Identification Method of Scientific Research Audit System Based On Distributed Machine Learning Algorithm
摘要
Abstract
In order to solve the problems of poor security,low precision and recall rate in scientific research audit system,a security vulnerability identification method of scientific research audit system based on distributed machine learning algorithm is designed.Collecting the user data of the scientific research audit system,clustering the user node data,introducing the concept of the k-nearest neighbor(KNN)algorithm to establish a network distributed structure model of the scientific research audit system,and combining and classifying the security vulnerability characteristics with representativeness and diversity.Based on distributed machine learning algorithm,security vulnerability identification is carried out in practical application.Two traditional security vulnerability identification methods are compared.The results show that the method can identify different types of security vulnerabilities,and the accuracy,precision and recall are improved.关键词
分布式机器学习算法/科研审计系统/安全漏洞识别/分布式结构模型/安全漏洞特征Key words
distributed machine learning algorithm/scientific research audit system/security vulnerability identification/distributed structure model/security vulnerability characteristics分类
信息技术与安全科学引用本文复制引用
李俊奕,肖亚纳..基于分布式机器学习算法的科研审计系统安全漏洞识别方法[J].兵工自动化,2025,44(6):48-51,81,5.基金项目
广东省科技计划项目(2020B1010010005) （2020B1010010005）
广东省科技专项资金项目(210901164532767) （210901164532767）
