基于数据挖掘技术的校园无线网络优化

Campus wireless network optimization based on data mining technology

针对现代校园网络的运行情况,校园无线网络的故障较多,并且容易受到网络攻击及病毒攻击,所以就实现了校园无线网络的改造升级。通过数据挖掘技术分析现有校园网络数据,将网络安全作为基础,分析现在校园无线网络上网量及已经出现的故障、网络攻击和木马等安全事件,结合相应的入侵检测及网络安全设备及软件功能的特点的考察,得到校园无线网络方案的优化。首先,利用数据技术聚类预测的方式得到网络正常或者不正常时候的部分规律,之后提出物理结构及逻辑结构网络优化方案,提出相应策略有效提高网络安全运行率及降低故障的发生机率。和入侵流程及工具特点相互结合进行全面的分析,综合之前方面,提出完善并且包括软件及硬件的安全优化方案,之后对其进行测试。根据测试表示,优化之后的校园无线网络能够合理使用带宽,避免出现网络安全事故,提高了用户使用效率。

In view of the operation of modern campus network,there are many failures in campus wireless network,and vulnerable to network attacks and virus attacks,so the transformation and upgrading of campus wireless network is realized.Technical analysis of the existing campus network data through data mining,network security as the basis,analysis of the campus wireless network and the Internet now,there have been the fault of network attacks and Trojans and other security incidents,to investigate the characteristics of the intrusion detection and network security equipment and software function,optimize the campus wireless network scheme.First,we use data technology to cluster and predict some rules of the network when it is normal or abnormal.After that,we put forward the network optimization scheme of physical structure and logical structure,and put forward corresponding strategies to effectively improve the network security operation rate and reduce the probability of failure.Combined with the characteristics of intrusion process and tools,a comprehensive analysis is carried out.A comprehensive safety optimization plan for software and hardware is put forward,and then tested.According to the test,the optimized campus wireless network can use the bandwidth reasonably,avoid the occurrence of network security accidents and improve the user's efficiency.