Detection of Leaps/sLumps in Traffic Volume of Internet Backbone

摘要：

This paper focuses on detecting anomalies in Internet backbone traffic.To monitor traffic on a scale of several terabits per second,we need to divide the time series data of a traffic volume into many slices.Therefore,we need to monitor a lot of traffic data.However,adjusting an appropriate threshold for each traffic time series data individually is difficult.To solve this problem,we propose an anomaly-detection algorithm that does not need parameters to be set for each time series data.This algorithm operates accurately with low computational complexity.A side-by-side test demonstrated that the accuracy of the algorithm was higher than that of the conventional method.Moreover,the necessary learning period of the algorithm was shorter than that of the conventional method.

关键词： Internet backbone traffic volume anomaly detection.

作者: Yutaka Hirokawa Kimihiro Yamamoto Shigeaki Harada Ryoichi Kawahara

作者单位: NIT Information Sharing Platform Laboratories,9-11,Midori-Cho 3-Chome,Musahino-shi,Tokyo,180-8585 Ja NTT Service Integration Laboratories,9-11,Midori-Cho 3-Chome,Musashino-shi,Tokyo,180-8585 Japan

会议类型: 国际会议

会议名称: 11th Asia-Pacific Network Operations and Management Symposium(APNOMS 2008)(第十一届亚太网络运行和管理国际研讨会)

会议地点: 北京

会议语种:英文

页码: 409-418

在线出版日期: 2008-10-22（万方平台首次上网日期，不代表论文的发表时间）