计算机工程Issue(3)：142-146,161,6.DOI:10.3969/j.issn.1000-3428.2015.03.027
基于数据流势能特征的分布式拒绝服务隐蔽流量检测
Distributed Denial of Service Covert Flow Detection Based on Data Stream Potential Energy Feature
吴娜 1穆朝阳 1张良春1
作者信息
- 1. 中国船舶重工集团公司第七一三研究所，郑州450000
- 折叠
摘要
Abstract
This paper introduces the current situation and development of Distributed Denial of Service( DDoS) attack, and proposes a flow potential energy analysis model based on time sequence, constructs sequence of network flow potential energy. It uses Auto Regression( AR) model to fit multi-dimensional parameter vector and describes the stability of network flow in unit time,and employs Support Vector Machine( SVM) based method to classify and train the target network flow character parameter vector,gains the best-matched network data flow potential energy set and final achieves accurate description of different DDoS attacks. It uses DARPA dataset,IXIA 400 network test machine and other software-hardware fundamentals to construct a real and analysis of the value network,validates the network flow potential energy analysis model based on the constructed network. Analysis and contrasts of the key indicators include DDoS detection accuracy, recognition rate, etc. Experimental results show that the method has higher detection precision and comprehensive better detection quality to DDoS.关键词
网络流量势能/分布式拒绝服务攻击/时间序列/流量检测/支持向量机/DARPA数据集Key words
network flow potential energy/Distributed Denial of Service ( DDoS ) attack/time sequence/flow detection/Support Vector Machine( SVM)/DARPA dataset分类
信息技术与安全科学引用本文复制引用
吴娜,穆朝阳,张良春..基于数据流势能特征的分布式拒绝服务隐蔽流量检测[J].计算机工程,2015,(3):142-146,161,6.
