%0 Journal Article
	%A Iosif-Viorel Onut and  Bin Zhu and  Ali A. Ghorbani
	%D 2007
	%J International Journal of Computer and Information Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 6, 2007
	%T Svision: Visual Identification of Scanning and Denial of Service Attacks
	%U https://publications.waset.org/pdf/7789
	%V 6
	%X We propose a novel graphical technique (SVision) for
intrusion detection, which pictures the network as a community of
hosts independently roaming in a 3D space defined by the set of
services that they use. The aim of SVision is to graphically cluster
the hosts into normal and abnormal ones, highlighting only the ones
that are considered as a threat to the network. Our experimental
results using DARPA 1999 and 2000 intrusion detection and
evaluation datasets show the proposed technique as a good candidate
for the detection of various threats of the network such as vertical
and horizontal scanning, Denial of Service (DoS), and Distributed
DoS (DDoS) attacks.
	%P 1741 - 1744