Distributed Denial of Service Covert Flow Detection Based on Data Stream Potential Energy Feature
Nengyou Wu · Jisuanji gongcheng · 2015
This paper introduces the current situation and development of Distributed Denial of Service(DDo S)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 DDo S attacks. It uses DARPA dataset,IXIA400 network test machine and other softwarehardware 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 DDo S detection accuracy,recognition rate,etc. Experimental results show that the method has higher detection precision and comprehensive better detection quality to DDo S.