DocumentCode :
3599829
Title :
Hadoop-based network traffic anomaly detection in backbone
Author :
Jishen Yu ; Feng Liu ; Wenli Zhou ; Hua Yu
Author_Institution :
Beijing Key Lab. of Network Syst. Archit. & Convergence, Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2014
Firstpage :
140
Lastpage :
145
Abstract :
This paper presents a distributed system for real-time anomaly detection in backbone. The backbone traffic is so huge that it is difficult to monitor abnormal traffic by traditional methods. Our system is based on Hadoop, an open source framework, and used to detect the abnormal traffic. Firstly, We establish a precise regression model to describe the network traffic. Secondly, distributed system Hadoop is used to detect the abnormal traffic. Finally, the experimental results prove that our system can detect the abnormal traffic accurately and efficiently in the real-world network environment.
Keywords :
computer network security; parallel processing; public domain software; regression analysis; telecommunication traffic; Hadoop-based network traffic anomaly detection; abnormal traffic monitor; backbone traffic; distributed system; open source framework; real-time anomaly detection; regression model; Probes; Telecommunication traffic; Anomaly Detection; Hadoop; backbone; traffic mode;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cloud Computing and Intelligence Systems (CCIS), 2014 IEEE 3rd International Conference on
Print_ISBN :
978-1-4799-4720-1
Type :
conf
DOI :
10.1109/CCIS.2014.7175718
Filename :
7175718
Link To Document :
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