Frequent sequential pattern discovery for data screening

Hisashi Tsuruta, Takayoshi Shoudai, Jun'ichi Takeuchi

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

1 Citation (Scopus)

Abstract

To early detect and defend the threats in the Internet caused by botnet, darknet monitoring is very important to understand various botnet activities. However, common illegal accesses by ordinary malwares makes such detection difficult. In this paper, in order to remove such accesses by ordinary malwares from the results of network monitoring, we propose a data screening method based on finding frequent sequential patterns which appear in given traffic data. Besides, we apply our method to traffic data observed in darknet and report the results.

Original languageEnglish
Title of host publicationIMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011
Pages315-322
Number of pages8
Publication statusPublished - Jul 26 2011
EventInternational MultiConference of Engineers and Computer Scientists 2011, IMECS 2011 - Kowloon, Hong Kong
Duration: Mar 16 2011Mar 18 2011

Publication series

NameIMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011
Volume1

Other

OtherInternational MultiConference of Engineers and Computer Scientists 2011, IMECS 2011
CountryHong Kong
CityKowloon
Period3/16/113/18/11

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Engineering(all)

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  • Cite this

    Tsuruta, H., Shoudai, T., & Takeuchi, J. (2011). Frequent sequential pattern discovery for data screening. In IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011 (pp. 315-322). (IMECS 2011 - International MultiConference of Engineers and Computer Scientists 2011; Vol. 1).