JCP 2014 Vol.9(6): 1426-1435 ISSN: 1796-203X
doi: 10.4304/jcp.9.6.1426-1435
doi: 10.4304/jcp.9.6.1426-1435
DDoS: Flood vs. Shrew
Zhijun Wu, Guang Li, Meng Yue, Hualong Zeng
Tianjin Key laboratory for Advanced Signal Processing, Civil Aviation University of China, Tianjin, 300300, China
Abstract—Distributed Denial of Service (DDoS) attack is one of the greatest threats to connectivity, continuity, and availability of the Internet. In this paper, two typical types of DDoS attacks, high-rate (Flood) and low-rate (Shrew), are studied on their generation principles, mechanism utilizations, behaviors, signatures, and attack performances. Experiment results show that: (I) high-rate DDoS sends a large amount of traffic to destroy the victim but it is easy to be detected. (II) low-rate DDoS organizes a small quantity of traffic to degrade the service quality at the victim end and it is easy to escape from detection. Comparison of flood with shrew is helpful to detect and defend DDoS attacks efficiently.
Index Terms—DDoS, High-Rate, Low-Rate, Flood, Shrew
Abstract—Distributed Denial of Service (DDoS) attack is one of the greatest threats to connectivity, continuity, and availability of the Internet. In this paper, two typical types of DDoS attacks, high-rate (Flood) and low-rate (Shrew), are studied on their generation principles, mechanism utilizations, behaviors, signatures, and attack performances. Experiment results show that: (I) high-rate DDoS sends a large amount of traffic to destroy the victim but it is easy to be detected. (II) low-rate DDoS organizes a small quantity of traffic to degrade the service quality at the victim end and it is easy to escape from detection. Comparison of flood with shrew is helpful to detect and defend DDoS attacks efficiently.
Index Terms—DDoS, High-Rate, Low-Rate, Flood, Shrew
Cite: Zhijun Wu, Guang Li, Meng Yue, Hualong Zeng, "DDoS: Flood vs. Shrew," Journal of Computers vol. 9, no. 6, pp. 1426-1435, 2014.
General Information
ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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