Title :
Data Mining Based Intrusion Detection System in VPN Application
Author :
Fan Ya-qin ; Fan Wen-yong ; Wang Lin-zhu
Author_Institution :
Coll. of Commun. Eng., Jilin Univ., Changchun, China
Abstract :
In order to solve the problem that the technology can not satisfy VPN consumer´s need about information insurance for the safety resolving tradition´s, in the main body of this essay, we have being aimed at it´s safe hidden trouble on the basis going deep into the operating principle studying VPN´s, have brought forward one kind of scheme, this scheme passes an introduction invade check system, excavate an introduction at the same time with the data arriving at invade have adopted to come to come true owing to that association regulation data excavates an algorithm in detecting system. Indicate result, compete with original network in relatively, this scheme has improved 60% to customer´s assurance coefficient. Be one kind of reliable protection measure, fall off or eliminate from the loss that network attack brings about, problem can not solve by the mechanism having resolved tradition protection.
Keywords :
data mining; security of data; virtual private networks; VPN application; customers assurance coefficient; data mining; introduction invade check system; intrusion detection system; virtual private network; Classification algorithms; Data mining; Data models; Intrusion detection; Itemsets; Virtual private networks; data mining; intrusion detection; virtual private network;
Conference_Titel :
Information Engineering (ICIE), 2010 WASE International Conference on
Conference_Location :
Beidaihe, Hebei
Print_ISBN :
978-1-4244-7506-3
Electronic_ISBN :
978-1-4244-7507-0
DOI :
10.1109/ICIE.2010.301