TIIS (한국인터넷정보학회)
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| 한글제목(Korean Title) |
A DoS Detection Method Based on Composition Self-Similarity |
| 영문제목(English Title) |
A DoS Detection Method Based on Composition Self-Similarity |
| 저자(Author) |
Zhu Jian-Qi
Fu Feng
Chong-kwon Kim
Yin Ke-xin
Liu Yan-Heng
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| 원문수록처(Citation) |
VOL 06 NO. 05 PP. 1463 ~ 1478 (2012. 05) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Based on the theory of local-world network, the composition self-similarity (CSS) of network traffic is presented for the first time in this paper for the study of DoS detection. We propose the concept of composition distribution graph and design the relative operations. The (R/S)d algorithm is designed for calculating the Hurst parameter. Based on composition distribution graph and Kullback Leibler (KL) divergence, we propose the composition self-similarity anomaly detection (CSSD) method for the detection of DoS attacks. We evaluate the effectiveness of the proposed method. Compared to other entropy based anomaly detection methods, our method is more accurate and with higher sensitivity in the detection of DoS attacks. |
| 키워드(Keyword) |
DoS detection
composition self-similarity
composition distribution graph
Kullback-Leibler divergence
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| 파일첨부 |
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