On the Need of Neuromorphic Twins to Detect Denial-of-Service Attacks on Communication Networks

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

Abstract

As we become more and more dependent on communication technologies, resilience against any attacks on communication networks is important to guarantee the digital sovereignty of our society. New developments of communication networks approach the problem of resilience through in-network computing approaches for higher protocol layers, while the physical layer remains an open problem. This is particularly true for wireless communication systems which are inherently vulnerable to adversarial attacks due to the open nature of the wireless medium. In denial-of-service (DoS) attacks, an active adversary is able to completely disrupt the communication and it has been shown that Turing machines are incapable of detecting such attacks. As Turing machines provide the fundamental limits of digital information processing and therewith of digital twins, this implies that even the most powerful digital twins that preserve all information of the physical network error-free are not capable of detecting such attacks. This stimulates the question of how powerful the information processing hardware must be to enable the detection of DoS attacks. Therefore, in this paper the need of neuromorphic twins is advocated and by the use of Blum-Shub-Smale machines a first implementation that enables the detection of DoS attacks is shown. This result holds for both cases of with and without constraints on the input and jamming sequences of the adversary.

Details

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalIEEE/ACM Transactions on Networking
Publication statusE-pub ahead of print - 14 Mar 2024
Peer-reviewedYes

Keywords

Keywords

  • 6G mobile communication, algorithmic detection, Blum-Shub-Smale machine, Denial-of-service attack, digital twin, Digital twins, Hardware, Jamming, jamming attack, neuromorphic computing, neuromorphic twin, Resilience, resilience, Turing machines