DocumentCode :
259692
Title :
Next Generation Application-Layer DDoS Defences: Applying the Concepts of Outlier Detection in Data Streams with Concept Drift
Author :
Stevanovic, Dusan ; Vlajic, Natalija
Author_Institution :
Dept. of Comput. Sci. & Eng., York Univ., Toronto, ON, Canada
fYear :
2014
fDate :
3-6 Dec. 2014
Firstpage :
456
Lastpage :
462
Abstract :
The existing state-of-the art in the field of application-layer DDoS protection is generally designed, and thus effective, only for static Web-domains. To the best of our knowledge, this paper is the first one to study the problem of application-layer DDoS defense in Web-sites of dynamic content and/or organization and under non-trivial bot (i.e., Attack) behavior. The main contributions of the paper are threefold: 1) we provide a detailed taxonomy of the existing and next-generation application-layer HTTP-based DDoS attacks, 2) we discuss the relevance of a branch of data mining theory -- known as data streams with concept drift -- to the problem of application-layer DDoS defense in dynamic Web-domains, 3) we present the outline of our next-generation anti-DDoS system that is intended for dynamic Web-domains facing different sophisticated variants of application-layer DDoS attacks. The paper also includes some of our preliminary experimental results concerning the detection of malicious Web-users/sessions using the proposed system.
Keywords :
Internet; Web sites; computer network security; data mining; Web site; concept drift; data mining; data stream; next generation application-layer DDoS protection; outlier detection; Browsers; CAPTCHAs; Computer crime; Crawlers; Next generation networking; Organizations; Taxonomy; application layer DDoS; data stream with concept drift; dynamic Web domain; intrusion detection & defence; outlier detection; simulation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications (ICMLA), 2014 13th International Conference on
Conference_Location :
Detroit, MI
Type :
conf
DOI :
10.1109/ICMLA.2014.80
Filename :
7033159
Link To Document :
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