NDLI: An Improved Wavelet Analysis Method for Detecting DDoS Attacks

Content Provider	IEEE Xplore Digital Library
Author	Liang Fu Lu Mao Lin Huang Orgun, M.A. Jia Wan Zhang
Copyright Year	2010
Abstract	Wavelet Analysis method is considered as one of the most efficient methods for detecting DDoS attacks. However, during the peak data communication hours with a large amount of data transactions, this method is required to collect too many samples that will greatly increase the computational complexity. Therefore, the real-time response time as well as the accuracy of attack detection becomes very low. To address the above problem, we propose a new DDoS detection method called Modified Wavelet Analysis method which is based on the existing Isomap algorithm and wavelet analysis. In the paper, we present our new model and algorithm for detecting DDoS attacks and demonstrate the reasons of why we enlarge the Hurst’s value of the self-similarity in our new approach. Finally we present an experimental evaluation to demonstrate that the proposed method is more efficient than the other traditional methods based on wavelet analysis.
Starting Page	318
Ending Page	322
File Size	425579
Page Count	5
File Format	PDF
ISBN	9781424484843
DOI	10.1109/NSS.2010.23
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-09-01
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Network intrusion detection Wavelet analysis Data mining Matrix decomposition Computer crime Distributed denial of service Nearest neighbor searches Wavelet coefficients Isomap algorithm Self-similarity
Content Type	Text
Resource Type	Article

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