Modular Neural Wiretap Codes for Fading Channels

Fuente: arXiv
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Autori principali: Seifert, Daniel, Günlü, Onur, Schaefer, Rafael F.
Natura: Preprint
Pubblicazione: 2024
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author Seifert, Daniel
Günlü, Onur
Schaefer, Rafael F.
author_facet Seifert, Daniel
Günlü, Onur
Schaefer, Rafael F.
contents The wiretap channel is a well-studied problem in the physical layer security literature. Although it is proven that the decoding error probability and information leakage can be made arbitrarily small in the asymptotic regime, further research on finite-blocklength codes is required on the path towards practical, secure communication systems. This work provides the first experimental characterization of a deep learning-based, finite-blocklength code construction for multi-tap fading wiretap channels without channel state information. In addition to the evaluation of the average probability of error and information leakage, we examine the designed codes in the presence of fading in terms of the equivocation rate and illustrate the influence of (i) the number of fading taps, (ii) differing variances of the fading coefficients, and (iii) the seed selection for the hash function-based security layer.
format Preprint
id arxiv_https___arxiv_org_abs_2409_08786
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Modular Neural Wiretap Codes for Fading Channels
Seifert, Daniel
Günlü, Onur
Schaefer, Rafael F.
Information Theory
Cryptography and Security
Machine Learning
The wiretap channel is a well-studied problem in the physical layer security literature. Although it is proven that the decoding error probability and information leakage can be made arbitrarily small in the asymptotic regime, further research on finite-blocklength codes is required on the path towards practical, secure communication systems. This work provides the first experimental characterization of a deep learning-based, finite-blocklength code construction for multi-tap fading wiretap channels without channel state information. In addition to the evaluation of the average probability of error and information leakage, we examine the designed codes in the presence of fading in terms of the equivocation rate and illustrate the influence of (i) the number of fading taps, (ii) differing variances of the fading coefficients, and (iii) the seed selection for the hash function-based security layer.
title Modular Neural Wiretap Codes for Fading Channels
topic Information Theory
Cryptography and Security
Machine Learning
url https://arxiv.org/abs/2409.08786