Optimally identifyingworm-infected hosts

Noriaki Kamiyama, Tatsuya Mori, Ryoichi Kawahara, Shigeaki Harada

Research output: Contribution to journalArticle

Abstract

We have proposed a method of identifying superspreaders by flow sampling and a method of filtering legitimate hosts from the identified superspreaders using a white list. However, the problem of how to optimally set parameters of f, the measurement period length, m*, the identification threshold of the flow count m within f, and H*, the identification probability for hosts with m = m*, remained unsolved. These three parameters seriously impact the ability to identify the spread of infection. Our contributions in this work are two-fold: (1) we propose a method of optimally designing these three parameters to satisfy the condition that the ratio of the number of active worm-infected hosts divided by the number of all vulnerable hosts is bound by a given upper-limit during the time T required to develop a patch or an anti-worm vaccine, and (2) the proposed method can optimize the identification accuracy of worm-infected hosts by maximally using a limited amount of memory resource of monitors.

Original languageEnglish
Pages (from-to)2084-2094
Number of pages11
JournalIEICE Transactions on Communications
VolumeE96-B
Issue number8
DOIs
Publication statusPublished - 2013 Aug
Externally publishedYes

    Fingerprint

Keywords

  • Detection
  • Optimum design
  • Sampling
  • Worm

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Software

Cite this