Identifying LDoS attack traffic based on wavelet energy spectrum and combined neural network

Author:

Yue Meng1ORCID,Liu Liang1ORCID,Wu Zhijun1,Wang Minxiao1

Affiliation:

1. School of Electronics and Information and Automation; Civil Aviation University of China; China

Funder

Natural Science Foundation of Tianjin City

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities of CAUC

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Reference39 articles.

1. A survey of defense mechanisms against distributed denial of service (DDoS) flooding attacks;Zargar;IEEE Commun Surv Tutorials,2013

2. Low-rate TCP-targeted denial of service attacks and counter strategies;Kuzmanovic;IEEE/ACM Trans Netwo,2006

3. Exploiting the transients of adaptation for RoQ attacks on Internet resources;Guirguis;IEEE Int Conf Netw Protocols,2004

4. Optimizing the pulsing denial-of-service attacks;Luo;Proc IEEE/IFIP Int Conf Dependable Sys Netw,2003

5. Modeling network traffic with multifractal behavior;Nogueira;Int Conf Telecommun,2005

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