Network Anomaly Detection Based on High-order AR Model

doi:10.3969/j.issn.1000-3428.2010.03.058

Computer Engineering ›› 2010, Vol. 36 ›› Issue (3): 174-176. doi: 10.3969/j.issn.1000-3428.2010.03.058

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Network Anomaly Detection Based on High-order AR Model

HUANG Qiang-sheng, CHENG Jiu-jun, KANG Qin-ma

(Department of Computer Science and Technology, College of Electronics and Information Engineering, Tongji University, Shanghai 201804)

Received:1900-01-01 Revised:1900-01-01 Online:2010-02-05 Published:2010-02-05

基于高阶AR模型的网络异常检测

黄强盛，程久军，康钦马

(同济大学电子与信息工程学院计算机科学与技术系，上海 201804)

Abstract

Abstract: This paper presents detection method based on 1-order AR model. Because of the low precision 1-order AR model owns, it proposes a method by substituting high-order AR model for 1-order one to make it more precise. Because setting the best parameters of the high-order AR model is an NP-complete problem, it applies genetic algorithm to search the better ones. Experiment shows that the high-order AR model is more efficient and precise for network anomaly detection.

Key words: network anomaly detection, AR model, genetic algorithm

摘要： 介绍基于1阶AR模型的检测方法，用高阶AR模型代替1阶AR模型以增加其精度。鉴于高阶AR模型最优参数的确定是个NP完全问题，利用遗传算法搜索其参数的近似最优解，通过实验验证高阶AR模型对网络异常检测的有效性和精确性。

关键词: 网络异常检测, AR模型, 遗传算法

CLC Number:

TP309

HUANG Qiang-sheng; CHENG Jiu-jun; KANG Qin-ma. Network Anomaly Detection Based on High-order AR Model[J]. Computer Engineering, 2010, 36(3): 174-176.

黄强盛;程久军;康钦马. 基于高阶AR模型的网络异常检测[J]. 计算机工程, 2010, 36(3): 174-176.

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