DocumentCode :
3705317
Title :
ID2T: A DIY dataset creation toolkit for Intrusion Detection Systems
Author :
Carlos Garcia Cordero;Emmanouil Vasilomanolakis;Nikolay Milanov;Christian Koch;David Hausheer;Max M?hlh?user
Author_Institution :
Telecooperation Group, Technische Universit?t Darmstadt / CASED, Germany
fYear :
2015
Firstpage :
739
Lastpage :
740
Abstract :
Intrusion Detection Systems (IDSs) are an important defense tool against the sophisticated and ever-growing network attacks. These systems need to be evaluated against high quality datasets for correctly assessing their usefulness and comparing their performance. We present an Intrusion Detection Dataset Toolkit (ID2T) for the creation of labeled datasets containing user defined synthetic attacks. The architecture of the toolkit is provided for examination and the example of an injected attack, in real network traffic, is visualized and analyzed. We further discuss the ability of the toolkit of creating realistic synthetic attacks of high quality and low bias.
Keywords :
"Intrusion detection","Computer crime","Entropy","Ports (Computers)","IP networks","Data mining","Data visualization"
Publisher :
ieee
Conference_Titel :
Communications and Network Security (CNS), 2015 IEEE Conference on
Type :
conf
DOI :
10.1109/CNS.2015.7346912
Filename :
7346912
Link To Document :
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