%0 Conference Proceedings
%T On Copulas-Based Classification Method for Intrusion Detection
%+ Université de Saïda
%+ Université du Québec à Trois-Rivières (UQTR)
%+ جامعة جيلالي اليابس [سيدي بلعباس، الجزائر] = Université Djillali Liabès [Sidi Bel Abbès, Algérie] = Djillali Liabes University [Sidi Bel Abbès, Algeria] (UDL)
%A Khobzaoui, Abdelkader
%A Mesfioui, Mhamed
%A Yousfate, Abderrahmane
%A Amar Bensaber, Boucif
%Z Part 11: Security and Network Technologies: Security
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 5th International Conference on Computer Science and Its Applications (CIIA)
%C Saida, Algeria
%Y Abdelmalek Amine
%Y Ladjel Bellatreche
%Y Zakaria Elberrichi
%Y Erich J. Neuhold
%Y Robert Wrembel
%I Springer International Publishing
%3 Computer Science and Its Applications
%V AICT-456
%P 394-405
%8 2015-05-20
%D 2015
%R 10.1007/978-3-319-19578-0_32
%K Intrusion detection
%K Classification
%K Copula function
%K Copula density estimator
%K Empirical copula
%Z Computer Science [cs]Conference papers
%X The intent of this paper is to develop a nonparametric classification method using copulas to estimate the conditional probability for an element to be a member of a connected class while taking into account the dependence of the attributes of this element. This technique is suitable for different types of data, even those whose probability distribution is not Gaussian. To improve the effectiveness of the method, we apply it to a problem of network intrusion detection where prior classes are topologically connected.
%G English
%Z TC 5
%2 https://inria.hal.science/hal-01789951/document
%2 https://inria.hal.science/hal-01789951/file/339159_1_En_32_Chapter.pdf
%L hal-01789951
%U https://inria.hal.science/hal-01789951
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-AICT-456
%~ IFIP-CIIA