Percolation Theory-Analysis of Malware Epidemics in Large-Scale Wireless Networks

  • Ainur Zhaikhan

Student thesis: Master's Thesis


The foreseen massive deployment of the internet of things (IoT) is expected to suffer from high security risks. This mainly results from the difficulty to monitor and cure the IoT devices in such large-scale deployment. In this thesis, we propose a spatial random deployment of special nodes (firewalls) which can detect and cure infected nodes within certain radius. An important concern is to add sufficient number of firewalls to make an epidemics finite and, hence, prevent malware outbreak over the whole network. The problem will be analyzed using percolation theory. Namely, we derive an upperbound for the critical intensity of spatial firewalls which guarantees prevention of large-scale network epidemics, regardless of the intensity of regular nodes. Using tools from percolation theory, we analyze the proposed solution and show the conditions required to ensure its efficiency.
Date of AwardApr 2020
Original languageEnglish (US)
Awarding Institution
  • Computer, Electrical and Mathematical Sciences and Engineering
SupervisorMohamed-Slim Alouini (Supervisor)


  • network epidemics
  • percolation theory
  • random graphs
  • wireless
  • communication network

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