基于跳频数据挖掘的校园网络入侵检测系统

Intrusion Detection System of Campus Network Based on Frequency Hopping Data Mining

随着计算机信息技术的快速发展,各大院校都在努力完善校园网信息建设,入侵检测系统就是其中的一种普遍应用,入侵检测技术的主动防御进攻概念是校园网的建设基础。基于此,笔者提出基于跳频数据挖掘的校园网络入侵检测系统。其硬件组成包括数据仓库、感应器、检查器、生成器等;软件设计包括数据包捕获模块、数据预处理模块和事件分析器模块。实验结果表明,本文设计的基于跳频数据挖掘的校园网络入侵检测系统在对入侵行为的检测上远胜于传统系统设计,无限趋近于100%,具有较高的有效性。

With the rapid development of computer information technology, colleges and universities are striving to improve the construction of campus network information. Intrusion detection system is one of the universal applications. The concept of active defense attack of intrusion detection technology is the foundation of campus network construction. Based on this, the author proposes a campus network intrusion detection system based on frequency hopping data mining. Its hardware consists of data warehouse, sensor, checker, generator, etc. Its software design includes data packet capture module, data preprocessing module and event analyzer module. The experimental results show that the campus network intrusion detection system based on frequency hopping data mining designed in this paper is much better than the traditional system design in Intrusion detection, infinitely approaching 100%, and has high effectiveness.