DocumentCode :
397936
Title :
Accelerating firewall through intelligent self-learning
Author :
Moon, Jongwook ; Park, Junku ; Jung, Gihyun ; Choi, Panan ; Kang, Youngu ; Choi, Kyunghee ; Noh, Sanguk
Author_Institution :
Dept. of Electron. Eng., Ajou Univ., Suwon, South Korea
Volume :
4
fYear :
2003
fDate :
5-8 Oct. 2003
Firstpage :
3524
Abstract :
A new approach to increase the throughput of firewall is proposed. Packet filtering and connection management usually done in firewall are relocated to the proposed firewall accelerator engine, named FA. FA also learns the behavior of firewall in an intelligent and unique way. With the knowledge acquired by the self-learning, FA can significantly reduce the number of packets to be fed to firewall and let firewall focus on content filtering that is widely used for protecting the Internet hackings. Some empirical studies show the proposed without changing the existing (or guessing) network configuration.
Keywords :
Internet; authorisation; embedded systems; unsupervised learning; Internet hackings; connection management; content filtering; embedded system; firewall accelerator engine; intelligent self-learning; network configuration; packet filtering; Acceleration; Bandwidth; Computer crime; Degradation; Filters; Hardware; Intrusion detection; Protection; Throughput; Virtual private networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2003. IEEE International Conference on
ISSN :
1062-922X
Print_ISBN :
0-7803-7952-7
Type :
conf
DOI :
10.1109/ICSMC.2003.1244435
Filename :
1244435
Link To Document :
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