A Probability Approach to Anomaly Detection with Twin Support Vector Machines  

作　　者：聂巍 何迪 

机构地区：[1]Department of Electronic Engineering, Shanghai Jiaotong University

出　　处：《Journal of Shanghai Jiaotong university(Science)》2010年第4期385-391,共7页上海交通大学学报（英文版）

基　　金：the National Natural Science Foundation of China (No. 60572157);the Scientific Research Foundation for the Returned Overseas Chinese Schol-ars, State Education Ministry

摘　　要：Classification of intrusion attacks and normal network flow is a critical and challenging issue in network security study. Many intelligent intrusion detection models are proposed, but their performances and efficiencies are not satisfied to real computer networks. This paper presents a novel effective intrusion detection system based on statistic reference model and twin support vector machines （TWSVMs）. Moreover, a network flow feature selection procedure has been studied and implemented with TWSVMs. The performances of proposed system are evaluated through using the fifth international conference on knowledge discovery and data mining in 1999 （KDD＇99） data set collected at MIT＇s Lincoln Labs and the results indicate that the proposed system is more efficient and effective than conventional support vector machines （SVMs） and TWSVMs.<Abstract>Classification of intrusion attacks and normal network flow is a critical and challenging issue in network security study. Many intelligent intrusion detection models are proposed, but their performances and efficiencies are not satisfied to real computer networks. This paper presents a novel effective intrusion detection system based on statistic reference model and twin support vector machines (TWSVMs). Moreover, a network flow feature selection procedure has been studied and implemented with TWSVMs. The performances of proposed system are evaluated through using the fifth international conference on knowledge discovery and data mining in 1999 (KDD’99) data set collected at MIT’s Lincoln Labs and the results indicate that the proposed system is more efficient and effective than conventional support vector machines (SVMs) and TWSVMs.

关 键 词：intrusion detection system (IDS) twin support vector machines (TWSVMs) PROBABILITY 

分 类 号：TP305[自动化与计算机技术—计算机系统结构]