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dc.contributor.authorWu, Yi-Chien_US
dc.contributor.authorTseng, Huei-Ruen_US
dc.contributor.authorYang, Wuuen_US
dc.contributor.authorJan, Rong-Hongen_US
dc.date.accessioned2014-12-08T15:37:51Z-
dc.date.available2014-12-08T15:37:51Z-
dc.date.issued2011en_US
dc.identifier.issn1743-8225en_US
dc.identifier.urihttp://hdl.handle.net/11536/26033-
dc.identifier.urihttp://dx.doi.org/10.1504/IJAHUC.2011.038998en_US
dc.description.abstractIn Distributed Denial-of-Service (DDoS) Attack, an attacker breaks into many innocent computers (called zombies). Then, the attacker sends a large number of packets from zombies to a server, to prevent the server from conducting normal business operations. We design a DDoS-detection system based on a decision-tree technique and, after detecting an attack, to trace back to the attacker's locations with a traffic-flow pattern-matching technique. Our system could detect DDoS attacks with the false positive ratio about 1.2-2.4%, false negative ratio about 2-10%, and find the attack paths in traceback with the false negative rate 8-12% and false positive rate 12-14%.en_US
dc.language.isoen_USen_US
dc.subjectDDoS detectionen_US
dc.subjectattacker tracebacken_US
dc.subjectdecision treeen_US
dc.subjectgrey relational analysisen_US
dc.titleDDoS detection and traceback with decision tree and grey relational analysisen_US
dc.typeArticleen_US
dc.identifier.doi10.1504/IJAHUC.2011.038998en_US
dc.identifier.journalINTERNATIONAL JOURNAL OF AD HOC AND UBIQUITOUS COMPUTINGen_US
dc.citation.volume7en_US
dc.citation.issue2en_US
dc.citation.spage121en_US
dc.citation.epage136en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000288319400006-
dc.citation.woscount5-
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