TY - GEN
T1 - Non-negative increment feature detection of the traffic throughput for early DDoS attack
AU - Huang, Ying
AU - Sun, Huizhong
AU - Chao, H. Jonathan
AU - Chao, Xiong
PY - 2007
Y1 - 2007
N2 - One of the major threats to cyber security is Distributed Denial of Service (DDoS) attacks. In this paper, we reveal the non-negative and cumulative increment effect of DDoS traffic throughput that is the feature accurately distinguished DDoS attacking traffic from normal flash crowd traffic. Our scheme can detect a DDoS attack in its early stages based on these feature. It can differentiate DDoS from flash crowd traffic effectively even if DDoS is potential. This scheme detects DDoS attacks with on-line and distributed characteristics. Simulation shows the algorithm's validity and accuracy.
AB - One of the major threats to cyber security is Distributed Denial of Service (DDoS) attacks. In this paper, we reveal the non-negative and cumulative increment effect of DDoS traffic throughput that is the feature accurately distinguished DDoS attacking traffic from normal flash crowd traffic. Our scheme can detect a DDoS attack in its early stages based on these feature. It can differentiate DDoS from flash crowd traffic effectively even if DDoS is potential. This scheme detects DDoS attacks with on-line and distributed characteristics. Simulation shows the algorithm's validity and accuracy.
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U2 - 10.1109/SITIS.2007.122
DO - 10.1109/SITIS.2007.122
M3 - Conference contribution
AN - SCOPUS:57849108523
SN - 9780769531229
T3 - Proceedings - International Conference on Signal Image Technologies and Internet Based Systems, SITIS 2007
SP - 121
EP - 126
BT - Proceedings - International Conference on Signal Image Technologies and Internet Based Systems, SITIS 2007
T2 - 3rd IEEE International Conference on Signal Image Technologies and Internet Based Systems, SITIS'07
Y2 - 16 December 2007 through 18 December 2007
ER -