河南城建学院学报Issue(6)：72-76,83,6.
基于OC-SVM的Hadoop DDoS攻击检测∗
Hadoop DDoS attack detection based on OC-SVM
摘要
Abstract
DDoS has been a major threat to the Internet. It has the characteristics of simple attack method, de-structiveness and untraceable. Research and application of cloud computing is being carried out. The Hadoop, as mainstream platform of cloud computing, faces the same serious threats of DDoS attack. Thus a new Hadoop DDoS distributed detection system based on one class SVM classification algorithm is proposed in this article. The mechanism of active learning and suspected attack verification are used in the new system, which can up-date the training set in real time, reduce the false positive rate and false negative rate effectively by using this method. It shows that the system has better classification accuracy, low false positive rate and false negative rate in experimental results.关键词
Hadoop/DDoS/OC-SVM/自主学习Key words
Hadoop/DDoS/OC-SVM/active Learning分类
信息技术与安全科学引用本文复制引用
洪家军..基于OC-SVM的Hadoop DDoS攻击检测∗[J].河南城建学院学报,2014,(6):72-76,83,6.基金项目
福建省教育厅国内访问学者资金资助项目 （）
福建省中青年教师教育科研资助项目(A类)( JA14279)。 （A类）
