On the Need of Neuromorphic Twins to Detect Denial-of-Service Attacks on Communication Networks
Holger Boche, Rafael F. Schaefer, H. Vincent Poor, and Frank H. P., Fitzek

TL;DR
This paper argues for the necessity of neuromorphic twins in communication networks to detect denial-of-service attacks, demonstrating a first implementation using Blum-Shub-Smale machines that surpasses Turing machine capabilities.
Contribution
It introduces the concept of neuromorphic twins for attack detection and provides a novel implementation using Blum-Shub-Smale machines to detect DoS attacks.
Findings
Neuromorphic twins are necessary for detecting DoS attacks.
Blum-Shub-Smale machines can implement attack detection beyond Turing limits.
Detection is effective with and without adversarial input constraints.
Abstract
As we are more and more dependent on the communication technologies, resilience against any attacks on communication networks is important to guarantee the digital sovereignty of our society. New developments of communication networks tackle the problem of resilience by 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…
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Taxonomy
TopicsAdvanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Quantum-Dot Cellular Automata
