The Early Detection of DDoS Based on the Persistent Increment Feature of the Traffic Volume

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22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008)

March 25-March 28

ISBN: 978-0-7695-3096-3

	ASCII Text	x
	Ying Huang, Xiangsheng Fu, Qiang Hou, Zifan Yu, "The Early Detection of DDoS Based on the Persistent Increment Feature of the Traffic Volume," Advanced Information Networking and Applications Workshops, International Conference on, pp. 365-370, 22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008), 2008.

	BibTex	x
	@article{ 10.1109/WAINA.2008.160, author = {Ying Huang and Xiangsheng Fu and Qiang Hou and Zifan Yu}, title = {The Early Detection of DDoS Based on the Persistent Increment Feature of the Traffic Volume}, journal ={Advanced Information Networking and Applications Workshops, International Conference on}, volume = {0}, year = {2008}, isbn = {978-0-7695-3096-3}, pages = {365-370}, doi = {http://doi.ieeecomputersociety.org/10.1109/WAINA.2008.160}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Advanced Information Networking and Applications Workshops, International Conference on TI - The Early Detection of DDoS Based on the Persistent Increment Feature of the Traffic Volume SN - 978-0-7695-3096-3 SP365 EP370 A1 - Ying Huang, A1 - Xiangsheng Fu, A1 - Qiang Hou, A1 - Zifan Yu, PY - 2008 KW - DDoS KW - Early Detection KW - Persistent Increment VL - 0 JA - Advanced Information Networking and Applications Workshops, International Conference on ER -

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WAINA.2008.160

One of the major threats to cyber security is Distributed Denial of Service (DDoS) attacks. In this paper, we propose a new algorithm based on the persistent increment tendency of DDoS traffic. Our scheme can detect a DDoS attack in its early stages when the attacking packet’s attribute value has no distinct features. It can differentiate DDoS from flash crowd traffic. This scheme detects DDoS attacks with on-line and distributed characteristics. Simulation shows the algorithm's validity and accuracy.

Index Terms:

DDoS, Early Detection, Persistent Increment

Citation:

Ying Huang, Xiangsheng Fu, Qiang Hou, Zifan Yu, "The Early Detection of DDoS Based on the Persistent Increment Feature of the Traffic Volume," ainaw, pp.365-370, 22nd International Conference on Advanced Information Networking and Applications - Workshops (aina workshops 2008), 2008

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