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Cluster-Based Countermeasures for DDoS Attacks

Cluster-Based Countermeasures for DDoS Attacks

Mohammad Jabed Morshed Chowdhury, Dileep Kumar G
Copyright: © 2016 |Pages: 22
ISBN13: 9781466687615|ISBN10: 1466687614|EISBN13: 9781466687622
DOI: 10.4018/978-1-4666-8761-5.ch008
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MLA

Chowdhury, Mohammad Jabed Morshed, and Dileep Kumar G. "Cluster-Based Countermeasures for DDoS Attacks." Network Security Attacks and Countermeasures, edited by Dileep Kumar G., et al., IGI Global, 2016, pp. 206-227. https://doi.org/10.4018/978-1-4666-8761-5.ch008

APA

Chowdhury, M. J. & Dileep Kumar G. (2016). Cluster-Based Countermeasures for DDoS Attacks. In D. G., M. Singh, & M. Jayanthi (Eds.), Network Security Attacks and Countermeasures (pp. 206-227). IGI Global. https://doi.org/10.4018/978-1-4666-8761-5.ch008

Chicago

Chowdhury, Mohammad Jabed Morshed, and Dileep Kumar G. "Cluster-Based Countermeasures for DDoS Attacks." In Network Security Attacks and Countermeasures, edited by Dileep Kumar G., Manoj Kumar Singh, and M.K. Jayanthi, 206-227. Hershey, PA: IGI Global, 2016. https://doi.org/10.4018/978-1-4666-8761-5.ch008

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Abstract

Distributed Denial of Service (DDoS) attack is considered one of the major security threats in the current Internet. Although many solutions have been suggested for the DDoS defense, real progress in fighting those attacks is still missing. In this chapter, the authors analyze and experiment with cluster-based filtering for DDoS defense. In cluster-based filtering, unsupervised learning is used to create profile of the network traffic. Then the profiled traffic is passed through the filters of different capacity to the servers. After applying this mechanism, the legitimate traffic will get better bandwidth capacity than the malicious traffic. Thus the effect of bad or malicious traffic will be lesser in the network. Before describing the proposed solutions, a detail survey of the different DDoS countermeasures have been presented in the chapter.

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