GrandDetAuto: Detecting malicious nodes in large-scale autonomous networks

Tigist Abera, Ferdinand Brasser, Lachlan Gunn, Patrick Jauernig, David Koisser, Ahmad Reza Sadeghi

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


Autonomous collaborative networks of devices are rapidly emerging in numerous domains, such as self-driving cars, smart factories, critical infrastructure, and Internet of Things in general. Although autonomy and self-organization are highly desired properties, they increase vulnerability to attacks. Hence, autonomous networks need dependable mechanisms to detect malicious devices in order to prevent compromise of the entire network. However, current mechanisms to detect malicious devices either require a trusted central entity or scale poorly. In this paper, we present GrandDetAuto, the first scheme to identify malicious devices efficiently within large autonomous networks of collaborating entities. GrandDetAuto functions without relying on a central trusted entity, works reliably for very large networks of devices, and is adaptable to a wide range of application scenarios thanks to interchangeable components. Our scheme uses random elections to embed integrity validation schemes in distributed consensus, providing a solution supporting tens of thousands of devices. We implemented and evaluated a concrete instance of GrandDetAuto on a network of embedded devices and conducted large-scale network simulations with up to 100 000 nodes. Our results show the effectiveness and efficiency of our scheme, revealing logarithmic growth in run-time and message complexity with increasing network size. Moreover, we provide an extensive evaluation of key parameters showing that GrandDetAuto is applicable to many scenarios with diverse requirements.

Original languageEnglish
Title of host publicationProceedings of 24th International Symposium on Research in Attacks, Intrusions and Defenses, RAID 2021
Number of pages15
ISBN (Electronic)9781450390583
Publication statusPublished - 7 Oct 2021
MoE publication typeA4 Article in a conference publication
EventInternational Symposium on Research in Attacks, Intrusions and Defenses - Virtual, Online, Spain
Duration: 6 Oct 20218 Oct 2021
Conference number: 24


ConferenceInternational Symposium on Research in Attacks, Intrusions and Defenses
Abbreviated titleRAID
CityVirtual, Online
Internet address


  • autonomous networks
  • malicious device detection
  • security


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