A regression method to compare network data and modeling data using generalized additive model

Sooyoung Chae, Hosub Lee, Jaeik Cho, Manhyun Jung, Jongin Lim, Jongsub Moon

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper suggests a method to check whether the real network dataset and modeling dataset for real network has statistically similar characteristics. The method we adopt in this paper is a Generalized Additive Model. By using this method, we show how similar the MIT/LL Dataset and the KDD CUP 99' Dataset are regarding their characteristics. It provided reasonable outcome for us to confirm that MIT/LL Dataset and KDD Cup Dataset are not statistically similar.

Original languageEnglish
Title of host publicationInformation Security Applications - 9th International Workshop, WISA 2008, Revised Selected Papers
Pages190-200
Number of pages11
DOIs
Publication statusPublished - 2009
Event9th International Workshop on Information Security Applications, WISA 2008 - Jeju Island, Korea, Republic of
Duration: 2008 Sep 232008 Sep 25

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5379 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Workshop on Information Security Applications, WISA 2008
CountryKorea, Republic of
CityJeju Island
Period08/9/2308/9/25

Keywords

  • Data set evaluation
  • Network data comparing
  • Statistical data analysis

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Chae, S., Lee, H., Cho, J., Jung, M., Lim, J., & Moon, J. (2009). A regression method to compare network data and modeling data using generalized additive model. In Information Security Applications - 9th International Workshop, WISA 2008, Revised Selected Papers (pp. 190-200). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5379 LNCS). https://doi.org/10.1007/978-3-642-00306-6_14