DocumentCode :
1690506
Title :
DDoS attack detection based on neural network
Author :
Li, Jin ; Liu, Yong ; Gu, Lin
Author_Institution :
Syst. Intell. Lab., Univ. of Aizu, Fukushima, Japan
fYear :
2010
Firstpage :
196
Lastpage :
199
Abstract :
DDoS attack is a major Internet security problem-DoS is that lots of clients simultaneously send service requests to certain server on the internet such that this server is too busy to provide normal services for others. Attackers using legitimate packets and often changing package information, so that traditional detection methods based on feature descriptions is difficult to detect it. This paper present an artificial intelligence DDoS attack detection method based on neural networks. In this method, analysis of server resources and network traffic, To training the ability of detection normal or abnormal, it have better results for detect DDoS attack.
Keywords :
Internet; artificial intelligence; computer network security; network servers; neural nets; packet switching; telecommunication traffic; DDoS attack detection; Internet security problem; artificial intelligence; legitimate packets; network traffic; neural network; package information; server resources; service requests; Accuracy; IP networks; Testing; Back Propagation Neural Network; Detection Rate; Distributed Denial of Service; False Negative; False Positive; LVQ Neural Network;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Aware Computing (ISAC), 2010 2nd International Symposium on
Conference_Location :
Tainan
Print_ISBN :
978-1-4244-8313-6
Type :
conf
DOI :
10.1109/ISAC.2010.5670479
Filename :
5670479
Link To Document :
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