Exploratory Performance Evaluation of VM Migration as MQTT Moving Target Defense
The Message Queuing Telemetry Transport (MQTT) protocol is a cornerstone of IoT communications. It relies on service brokers to enable reliable data delivery between devices and clients. In modern deployments, MQTT brokers are frequently hosted in virtualized environments to support scalability, flexibility, and resource efficiency. However, virtualization enlarges the attack surface, posing challenges to service reliability and security. This paper investigates the use of Virtual Machine (VM) migration as a Moving Target Defense (MTD) to enhance security in MQTT-based IoT services. While VM migration is an established technique in network and service management for workload balancing and fault tolerance, its impact, when used as a proactive security mechanism in MQTT deployments, remains unexplored. This work shows a comprehensive performance evaluation of VM migration under both normal and active attack scenarios. The results demonstrate that the security benefits of VM migration come with minimal performance degradation, characterized by a modest effect size (Cohen D measure<0.5), thus ensuring service continuity and operational stability. However, it comes with a cost of increased performance oscillation (i.e., higher incidences of peaks in the response time). This paper also introduces an interactive, web-based tool that enables pre-deployment MTD simulation. This work offers insights into integrating security-aware VM migration within IoT service management.
Authors
- Denis Rosário
- Michele Carraschi Nogueira
- Tiago Cruz (ORCID: https://orcid.org/0000-0002-3645-259X)
- Matheus Torquato (ORCID: https://orcid.org/0000-0002-5868-2919)
- Eduardo Cerqueira
Institutions
- Universidade Federal de Minas Gerais (BR)
- University of Coimbra (PT)
Publication Details
- Published
- 2025-10-27
- DOI
- https://doi.org/10.23919/cnsm67658.2025.11297545
- Primary Topic
- Software-Defined Networks and 5G
- Type
- article
- Field-Weighted Citation Impact
- 0.00