Malware propagation in large-scale networks

Shui Yu, Guofei Gu, Ahmed Barnawi, Song Guo, Ivan Stojmenovic

Research output: Journal article publicationJournal articleAcademic researchpeer-review

88 Citations (Scopus)

Abstract

Malware is pervasive in networks, and poses a critical threat to network security. However, we have very limited understanding of malware behavior in networks to date. In this paper, we investigate how malware propagates in networks from a global perspective. We formulate the problem, and establish a rigorous two layer epidemic model for malware propagation from network to network. Based on the proposed model, our analysis indicates that the distribution of a given malware follows exponential distribution, power law distribution with a short exponential tail, and power law distribution at its early, late and final stages, respectively. Extensive experiments have been performed through two real-world global scale malware data sets, and the results confirm our theoretical findings.
Original languageEnglish
Article number6807753
Pages (from-to)170-179
Number of pages10
JournalIEEE Transactions on Knowledge and Data Engineering
Volume27
Issue number1
DOIs
Publication statusPublished - 1 Jan 2015
Externally publishedYes

Keywords

  • Malware
  • Modelling
  • Power law
  • Propagation

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics

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