Malware Containment Via Firewall Placement in Iot Networks

Wessam Mesbah*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

One of the biggest risks that wireless IoT networks encounter is malware or botnet epidemics. Malware can propagate from one device to another device that exists in its coverage range as long as there are no check points (firewalls) to protect that device. Firewalls can be hardware (special devices) or software licensed to be activated on a limited number of devices. Unfortunately, in both cases the number of firewalls that can be installed in any network is limited due to cost constraints. Therefore, it is mandatory to make efficient use of that available number of firewalls. In this paper we consider optimization of the firewall placement in a massive IoT network. The objective of the optimization problem is to reduce the number of firewalls required to divide the network into a given number of virtually isolated clusters. This clustering problems is non-convex and is known to be NP- hard. However, we provide an efficient algorithm to solve it, and we compare its performance to the well known K-Means clustering algorithm. Simulation results show that the average performance of the proposed algorithms outperforms performance of the the K-Means algorithm. Although many network clustering algorithms have been considered in the literature with different objectives, to the best of our knowledge, the objective of the clustering considered in this paper has not been considered before. Furthermore, the proposed clustering algorithm does not contradict with any other clustering objective. Once the firewalls are placed, any other clustering algorithm can be used to satisfy a different objective.

Original languageEnglish
Title of host publication2025 IEEE 101st Vehicular Technology Conference, VTC 2025-Spring 2025 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331531478
DOIs
StatePublished - 2025
Event101st IEEE Vehicular Technology Conference, VTC 2025-Spring 2025 - Oslo, Norway
Duration: 17 Jun 202520 Jun 2025

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1550-2252

Conference

Conference101st IEEE Vehicular Technology Conference, VTC 2025-Spring 2025
Country/TerritoryNorway
CityOslo
Period17/06/2520/06/25

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

Keywords

  • Clustering
  • Graph Partitioning
  • IoT
  • Malware Epidemics
  • Spatial Firewalls
  • Wireless Ad-Hoc Networks

ASJC Scopus subject areas

  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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