基于聚类算法的网络信息安全检测与跟踪系统研究
Research on Network Information Security Detection and Tracking System Based on Clustering Algorithm
胡玉琴 1朱博逸2
作者信息
- 1. 鹤壁市机电信息工程学校,河南鹤壁 458030
- 2. 白俄罗斯国立技术大学,明斯克 220013
- 折叠
摘要
为提升网络信息安全检测效率和准确性,文章简要探讨聚类算法在网络异常行为识别、流量分析及恶意软件检测等关键领域的应用,并设计一个基于聚类算法的网络信息安全检测与跟踪系统.研究结果表明,聚类算法能够有效地在大规模、动态变化网络数据中识别出潜在安全威胁,可提升安全事件检测速度和准确率.基于聚类算法的网络信息安全检测与跟踪系统能够更加高效地处理网络威胁,增强网络信息安全的防护能力.
Abstract
In order to improve the efficiency and accuracy of network information security detection,this paper discusses the application effect of clustering algorithm in the key fields such as network abnormal behavior identification,traffic analysis and malicious software detection,and designs a network information security detection and tracking system based on clustering algorithm.The results show that the clustering algorithm can effectively identify potential security threats in large-scale and dynamic changing network data,and can improve the speed and accuracy of security event detection.The network information security detection and tracking system based on clustering algorithm can deal with network threats more efficiently and enhance the ability of network information security protection.
关键词
聚类算法/网络信息安全/功能模块Key words
clustering algorithm/network information security/function module引用本文复制引用
基金项目
2020年河南省教育厅规划课题(zjb20062)
出版年
2024
NETL
NSTL
万方数据