A table-driven approach for IP traceback based on network statistic analysis

Authors:
Wei-Tsung Su;Yi-Hsun Chuang;Zong-Bing Wu;Yau-Hwang Kuo
Affiliations:
Department of Computer Science and Information Engineering, Aletheia University, Taipei Country, Taiwan, R.O.C.;Center for Research of E-life DIgital Technology, Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan, R.O.C.;Center for Research of E-life DIgital Technology, Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan, R.O.C.;Center for Research of E-life DIgital Technology, Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan, Taiwan, R.O.C.
Venue:
ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 3
Year:
2009

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Abstract

IP-spoofed DDoS attack is a serious security problem in Internet. Thus, an IP traceback approach is essential. In this paper, a fast IP traceback approach (FTA) based on network statistic analysis is proposed. By maintaining the Branch Label Table (BLT) which contains some network statistics in edge routers, the time of IP traceback procedure is efficiently reduced. In addition, an adaptive packet filter is proposed to mitigate the DDoS attacks. The packet drop rate adapts to the location of DDoS attackers and the queue length. Finally, ns-2 simulation is conducted to evaluate FTA. The simulation results show FTA substantially accelerates IP traceback procedure. Moreover, the proposed adaptive packet filter efficiently mitigates the DDoS attacks.