HLR_DDoS: A Low-Rate and High-Rate DDoS Attack Detection Method Using $$\alpha $$α-Divergence View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018

AUTHORS

Nazrul Hoque , Dhruba K. Bhattacharyya

ABSTRACT

In this paper, an effective method called HLR_DDoS is proposed to detect both low- and high-rate flooding attacks using a statistical approach. The method detects both types of attacks in two steps: (i) normal traffic analysis using cross-correlation measure and (ii) identification of suspicious high- and low-rate attack traffic using \(\alpha \)-divergence. The proposed method is evaluated on DDoS CAIDA 2007 and DARPA 2000 datasets. More... »

PAGES

655-662

Book

TITLE

Proceedings of the International Conference on Computing and Communication Systems

ISBN

978-981-10-6889-8
978-981-10-6890-4

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-981-10-6890-4_63

DOI

http://dx.doi.org/10.1007/978-981-10-6890-4_63

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1103779939


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