Evaluating Trustworthiness of Edge-Based Multi-Tenanted IoT Devices

Internet of Things (IoT) systems are expected to be deployed as solutions to problems in a wide variety of contexts, from building management, to smart city monitoring and to provide support to emergency services. However, many IoT devices are resource constrained and lack the capability or information to compute results for tasks that the IoT devices may be requested to perform. Instead these tasks will need to be offloaded to a server at the Edge of the network for a quick response. As these networks will have multiple organisations providing multiple IoT nodes and Edge nodes with different capabilities, the IoT devices need to know which Edge server they trust to return a timely response to a task. As these networks will support critical services, they also need to be resilient to attack.

Thus far the project has delivered a prototype middleware to support trust-based task offloading in a system comprised of resource-constrained devices. The performance of this middleware was investigated and published at the ACM Symposium of Applied Computing. We have also investigated performing a proactive trust assessment which has been published at IEEE INFOCOM.


Role: Research Co-Investigator

Duration: March 2020 – March 2021




  • Matthew Bradbury, Arshad Jhumka, and Tim Watson. Trust Assessment in 32 KiB of RAM: Multi-application Trust-based Task Offloading for Resource-constrained IoT Nodes. In The 36th ACM/SIGAPP Symposium on Applied Computing, SAC'21, 1–10. Virtual Event, Republic of Korea, 22–26 March 2021. ACM. doi:10.1145/3412841.3441898.
    [bibtex] [file] [presentation] [dataset]
  • Matthew Bradbury, Arshad Jhumka, and Tim Watson. Trust Trackers for Computation Offloading in Edge-Based IoT Networks. In IEEE INFOCOM, 1–10. Virtual Event, Canada, 10–13 May 2021. IEEE.
    [bibtex] [file] [presentation] [dataset]