计算机工程与科学2017，Vol.39Issue(12)：2185-2191,7.DOI:10.3969/j.issn.1007-130X.2017.12.004
一种Hadoop集群下的行为异常检测方法
An abnormal behavior detection method in Hadoop cluster
摘要
Abstract
With the development of distributed computing technology,Hadoop,as a typical representative in the field of massive data processing,is vulnerable to hidden security threats,such as data breaches,due to weak security mechanism and lack of user activity monitoring.By combining with the characteristics of the principal component analysis,we perform parallel process through MapReduce to overcome the disadvantage of principal component analysis and improve the training efficiency.We propose an abnormal behavior detection method in Hadoop cluster,namely we compare the current user behavior patterns with historical behavior patterns to see if they match,which is taken as a metric for anomaly behavior detection.Experimental results indicate that our method can detect users' anomaly behavior effectively.关键词
Hadoop集群/主成分分析/异常检测/MapReduce/行为模式Key words
Hadoop cluster/principal component analysis/anomaly detection/MapReduce/behavior pattern分类
信息技术与安全科学引用本文复制引用
蔡武越,王珂,郝玉洁,段晓冉..一种Hadoop集群下的行为异常检测方法[J].计算机工程与科学,2017,39(12):2185-2191,7.基金项目
国家自然科学基金联合基金项目(U1230106) （U1230106）
国家信息安全242项目(2013A050) （2013A050）
