Analysis and detection on long-time quasi-periodic communication behavior of network applications

摘要：

　　Internet applications with long-time quasi-periodic (LTQP) communication behavior are always sensitive and critical in traffic monitoring,safety detection,user billing etc.Analysis and detection on such behavior can provide help for the identification of ”always online” applications,which is of great significance.This paper first introduces the concept of LTQP communication behavior,then study the inter packet time (IPT) distribution and typical packet group pattern of LTQP communication traffic in detail,finally constructs a cascading structure identification method to stepwise detect LTQP communication behavior,and verifies the performance by experiment.

关键词： traffic monitoring always online long-time quasi-periodic inter packet group time machine learning

作者: LIU Fang LI Chen-yu OUYANG Shu-xin CHEN Lu-ying

作者单位: School of Information and Communication Engineering,Beijing University of Posts and Telecommunications,Beijing 100876,China

会议类型: 国内会议

会议名称: 第六届中国传感器网络学术会议(CWSN 2012)

会议地点: 黄山

会议语种:英文

页码: 80-85,159

在线出版日期: 2012-10-25（万方平台首次上网日期，不代表论文的发表时间）