On modeling eavesdropping attacks in wireless networks

Xuran Li, Jianlong Xu, Hong-Ning Dai*, Qinglin Zhao, Chak Fong Cheang, Qiu Wang

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

24 Citations (Scopus)


This paper concerns the eavesdropping attacks from the eavesdroppers' perspective, which is new since most of current studies consider the problem from the good nodes' perspective. In this paper, we originally propose an analytical framework to quantify the effective area and the probability of the eavesdropping attacks. This framework enables us to theoretically evaluate the impact of node density, antenna model, and wireless channel model on the eavesdropping attacks. We verify via extensive simulations that the proposed analytical framework is very accurate. Our results show that the probability of eavesdropping attacks significantly vary, depending on the wireless environments (such as shadow fading effect, node density, and antenna types). This study lays the foundation toward preventing the eavesdropping attacks in more effective and more economical ways.

Original languageEnglish
Pages (from-to)196-204
Number of pages9
JournalJournal of Computational Science
Publication statusPublished - Nov 2015

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)
  • Modelling and Simulation

User-Defined Keywords

  • Eavesdropping
  • Modeling
  • Security
  • Wireless networks


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