基于数据挖掘的入侵检测框架  

The Framework of Intrusion Detection Based on Data Mining

作　　者：陈丽珊[1] CHEN Li-shan(Putian Branch, The Open University of Fujian, Putian 351100, China)

机构地区：[1]福建广播电视大学莆田分校,福建莆田351100

出　　处：《西安文理学院学报（自然科学版）》2016年第6期35-38,共4页Journal of Xi’an University(Natural Science Edition)

摘　　要：近些年来计算机网络得到高速发展,成为信息传递的重要途径,也成为信息技术领域的热门课题.其中一个研究重点就是因网络入侵引发的安全风险问题,如何有效地检测和防范入侵行为是信息监管过程中的重要内容.混合框架采用数据挖掘技术,实现了入侵检测模型的构建.随着数据挖掘技术在入侵检测领域的广泛应用,方法繁多且系统不成体系一度成为研究过程中的重要问题.显然采用直接系统的框架模型,可以成为提高效率的一种方式.基于数据挖掘的入侵检测框架,可以有效地解决以上问题并提高系统化程度,改善入侵检测的准备效率与自适应能力.In recent years, with the rapid development of computer network, it is one of the im- portant ways of information transmission, and it has become an important research part in the field of information technology. One of the research focuses on the network intrusion due to the risk of security problems, how to detect and prevent intrusion behavior effectively and efficiently is an important content in the process of information monitoring. The hybrid framework adopts data mining technology to realize the construction of intrusion detection model. With the exten- sive application of data mining technology in the field of intrusion detection, a wide range of methods and the system is not a system has become an important issue in the process of re- search. Obviously, using the direct system framework model, it can be a way to improve the ef- ficiency. Data mining based intrusion detection framework can effectively solve the above prob- lems, improve the degree of system, and improve the efficiency of intrusion detection and adap- tive capacity.

关 键 词：数据挖掘 入侵检测 模型框架 日志安全 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]