DocumentCode
3772292
Title
Pippy Search: Anomaly Traffic Clustering
Author
Lili Yang;Jie Wang;Mansoor Ahmed Khuhro
Author_Institution
Sch. of Inf. Sci. &
fYear
2015
Firstpage
378
Lastpage
383
Abstract
Terrible network environment is damaging the critical infrastructure and the interests of internet users. In order to ensure the protection and resilience of attack, it is important to better analyze and observe network traffic for discovering anomaly. This paper presents a clustering algorithm by using network-layer and transport-layer statistical feature to classify anomaly traffic. Experiments with public datasets show the proposed algorithm has a significant effectiveness of traffic clustering quality.
Keywords
"Clustering algorithms","Classification algorithms","Payloads","Computer crime","Algorithm design and analysis","Internet","Feature extraction"
Publisher
ieee
Conference_Titel
Smart City/SocialCom/SustainCom (SmartCity), 2015 IEEE International Conference on
Type
conf
DOI
10.1109/SmartCity.2015.101
Filename
7463755
Link To Document