Malware Tolerant (Mesh-) Networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Colleges, School and Institutes


Mesh networks, like e.g. smart-homes, are networks where every node has routing capabilities. These networks are usually flat, which means that one compromised device can potentially overtake the whole infrastructure, especially considering clone attacks.
To counter attacks, we propose a network architecture which enhances flat networks, especially mesh networks, with isolation and automatic containment of malicious devices. Our approach consists of unprivileged devices, clustered into groups, and privileged “bridge” devices which can cooperatively apply filter rules like a distributed firewall. Since there is no ultimate authority (not even bridges) to control the whole network, our approach has no single point-of-failure – so-called intrusion or malware tolerance. That means, attacks on a single device will not compromise the whole infrastructure and are tolerated. Previous research on mesh networks [10, 3, 8, 9] relied on a single point-of-failure and is, thus, not intrusion or malware tolerant.
Our architecture is dynamic in the sense that bridge devices can change, misbehaving devices can be isolated by outvoting them, and cryptographic keys evolve. This effectively turns the entire network into a moving target.
We used the protocol verifier ProVerif to prove the security properties of our network architecture.


Original languageEnglish
Title of host publicationProceedings of the 17th International Conference on Cryptology And Network Security (CANS 2018)
Publication statusPublished - 1 Sep 2018
Event17th International Conference on Cryptology And Network Security (CANS 2018) - Naples, Italy
Duration: 30 Sep 20183 Oct 2018

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference17th International Conference on Cryptology And Network Security (CANS 2018)


  • mesh network, malware tolerance, self-management, network security