基于关联规则挖掘的智能云防护技术研究  

Study on the Intelligent Cloud Protection Technology based on Association Rule Mining

作　　者：方忠进[1,2,3] 夏志华[1,3] 周舒[1,3] 

机构地区：[1]南京信息工程大学计算机与软件学院,江苏南京210044 [2]南京信息工程大学滨江学院,江苏南京210044 [3]南京信息工程大学江苏省网络监控工程中心,江苏南京210044

出　　处：《通信技术》2014年第8期925-929,共5页Communications Technology

摘　　要：针对传统安全防护技术存在的被动防御、效率较低的缺陷,提出了一种基于关联规则挖掘的智能云防护技术。该技术引入一种改进的FP-Growth挖掘算法,用来提取数据的特征信息,提交到云端,通过将此特征信息与入侵特征库和网络正常活动行为特征库进行匹配,从而发现病毒和攻击行为。特征库根据庞大的云探针系统采集的数据样本不断更新完善。实验结果表明,基于改进的FP-Growth挖掘算法的智能云防护技术对攻击行为响应较快,检测效率较高,准确记录攻击日志,具有较好的安全防护性能。According to the limit of passive defense and low detection efficiency of traditional security technology, an intelligent cloud protection technology based on association rule mining is proposed. An improved FP-Growth algorithm is applied to extract the feature information of data. The feature information is matched with intrusion feature database and normal activities feature database to detect viruses and attacks. Feature database is continuously updated and improved according to the data samples collected by the huge cloud probe system. Experimental results show that the intelligent cloud protection technology based on the improved FP-Growth algorithm can detect attacks in time, and record attack log accurately. It has a high detection efficiency and good protection performance.

关 键 词：关联规则 云安全 FP-GROWTH算法 数据挖掘 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]