Battery draining attacks against edge computing nodes in IoT networks

Ryan T Smith, Daniel Palin, Philokypros P. Ioulianou*, Vasileios Vasilakis, Siamak F. Shahandashti

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Many IoT devices, especially those deployed at the network edge have limited power resources. In this work, we study the effects of a variety of battery draining attacks against edge nodes. Specifically, we implemented hello flooding, packet flooding, selective forwarding, rank attack, and versioning attack in ContikiOS and simulated them in the Cooja simulator. We consider a number of relevant metrics, such as CPU time, low power mode time, TX/RX time, and battery consumption. Besides, we test the stretch attack with three different batteries as an extreme scenario. Our results show that versioning attack is the most severe in terms of draining the power resources of the network, followed by packet flooding and hello flooding attacks. Furthermore, we find that selective forwarding and rank attacks are not able to considerably increase the power resource usage in our scenarios. By quantifying the effects of these attacks, we demonstrate that under specific scenarios, versioning attack can be three to four times as effective as packet flooding and hello flooding attacks in wasting network resources. At the same time, packet flooding is generally comparable to hello flooding in CPU and TX time usage increase but twice as powerful in draining device batteries.

Original languageEnglish
Number of pages21
JournalCyber-Physical Systems
Early online date20 Jan 2020
Publication statusE-pub ahead of print - 20 Jan 2020

Bibliographical note

© 2020 Informa UK Limited, trading as Taylor & Francis Group. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details.


  • battery draining attacks
  • Contikios
  • Cooja
  • Edge computing
  • Internet of Things
  • smart sensors

Cite this