DocumentCode :
3575145
Title :
Bivariate Non-parametric Anomaly Detection
Author :
Callegari, Christian ; Giordano, Stefano ; Pagano, Michele
Author_Institution :
Dept. of Inf. Eng., Univ. of Pisa, Pisa, Italy
fYear :
2014
Firstpage :
810
Lastpage :
813
Abstract :
Detecting anomalous traffic with low false alarm rates is of primary interest in IP networks management. In this paper we propose a novel anomaly detection system, based on a combined use of sketches and of a novel bivariate non-parametric detection method. The latter allows us to simultaneously analyse two different traffic features so as to improve the performance of the "classical" detection systems, in terms of both detection rate and false alarm rate. The preliminary performance analysis, presented in this paper, demonstrates the effectiveness of the proposed system.
Keywords :
IP networks; computer network management; computer network security; telecommunication traffic; IP networks management; anomalous traffic detection; bivariate nonparametric anomaly detection; bivariate nonparametric detection method; detection rate; false alarm rates; traffic features; Aggregates; Algorithm design and analysis; Conferences; Entropy; IP networks; Internet; Measurement; Anomaly Detection; Sketch; bivariate nonparametric algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
High Performance Computing and Communications, 2014 IEEE 6th Intl Symp on Cyberspace Safety and Security, 2014 IEEE 11th Intl Conf on Embedded Software and Syst (HPCC,CSS,ICESS), 2014 IEEE Intl Conf on
Print_ISBN :
978-1-4799-6122-1
Type :
conf
DOI :
10.1109/HPCC.2014.132
Filename :
7056836
Link To Document :
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