基于数据挖掘技术的网络安全监测分析
Network security monitoring and analysis based on data mining technology
文成 1徐良 1席茜2
作者信息
- 1. 信阳学院,河南信阳 464000
- 2. 南湾水库事务中心,河南信阳 464000
- 折叠
摘要
[目的/意义]面向不同网络平台的数据加密传输、数据挖掘和聚类分析,已经成为企事业单位网络安全关注的重要问题.[方法/过程]对于不同类型网络攻击使用大数据挖掘的算法技术,提出基于改进Apriori算法的关联规则数据挖掘、网络攻击入侵检测模式.[结果/结论]引入二数据分块和二叉树拼接规则,过滤无意义的初始数据,将多列数据划分为N块子矩阵,计算每个子矩阵的频繁项集并拼接为最大频繁项集,实现最快、最优的数据挖掘和算法收敛,提升了网络安全数据监测的准确率.
Abstract
[Purpose/Significance]Data encryption transmission,data mining,and clustering analysis for different network platforms have become important issues of network security concern for enterprises and institutions.[Method/Process]The algorithm technology of big data mining is required for different types of network attacks,and an association rule data mining and network attack intrusion detection mode based on the improved Apriori algorithm is proposed.[Results/Conclusion]Introducing binary data partitioning and binary tree concatenation rules,filtering meaningless initial data,dividing multi column data into N block submatrixes,calculating the frequent itemsets of each submatrix and concatenating them into the maximum frequent itemset,thereby achieving the fastest and optimal data mining and algorithm convergence,and improving the accuracy of network security data monitoring.
关键词
数据挖掘/改进Apriori算法/网络安全/监测/数据安全Key words
data mining/improve the Apriori algorithm/network security/monitoring/data security引用本文复制引用
基金项目
校级科研项目(2022-XJLYB-017)
出版年
2024
NETL
NSTL
万方数据