Worm path identification using visualization system

Seiji Shibaguchi, Yuki Nakayama, Ken Ichi Okada

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

1 Citation (Scopus)

Abstract

In this paper, we propose a visualization system for worm investigation, which finds worm origins and worm paths. Although investigation of worms are very important for forensic use and further prevention, it is quite difficult for automatic systems to identify worm origins or paths due to the trade-off between false positives and false negatives. Therefore, we focused on interaction between analysts and connection logs. At first, an automated algorithm is run so that there are no false negatives, and then analysts investigate the result to reduce false positives by visualized system. We aim to solve the trade-off by conducting these two steps. We implemented a prototype and conducted a user experiment to evaluate our system. The results show our system enabled subjects to reduce 90% of false detection by an automated algorithm. Although the results depend on parameters or conditions, we show the effectiveness of our idea.

Original languageEnglish
Title of host publicationProceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009 - 2009 IEEE International Conference on Privacy, Security, Risk, and Trust, PASSAT 2009
Pages498-503
Number of pages6
DOIs
Publication statusPublished - 2009 Dec 4
Event2009 IEEE International Conference on Privacy, Security, Risk, and Trust, PASSAT 2009 - Vancouver, BC, Canada
Duration: 2009 Aug 292009 Aug 31

Publication series

NameProceedings - 12th IEEE International Conference on Computational Science and Engineering, CSE 2009
Volume3

Other

Other2009 IEEE International Conference on Privacy, Security, Risk, and Trust, PASSAT 2009
CountryCanada
CityVancouver, BC
Period09/8/2909/8/31

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Software

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