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Related papers: Deep Learning for the Gaussian Wiretap Channel

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We consider the problem of covert communication with random slot selection over binary-input Discrete Memoryless Channels and Additive White Gaussian Noise channels, in which a transmitter attempts to reliably communicate with a legitimate…

Information Theory · Computer Science 2025-07-21 Shi-Yuan Wang , Keerthi S. K. Arumugam , Matthieu R. Bloch

This paper studies the frequency/time selective $K$-user Gaussian interference channel with secrecy constraints. Two distinct models, namely the interference channel with confidential messages and the one with an external eavesdropper, are…

Information Theory · Computer Science 2016-11-17 Onur Ozan Koyluoglu , Hesham El Gamal , Lifeng Lai , H. Vincent Poor

Semantic communication is an increasingly popular framework for wireless image transmission due to its high communication efficiency. With the aid of the joint-source-and-channel (JSC) encoder implemented by neural network, semantic…

Information Theory · Computer Science 2022-12-02 Maojun Zhang , Yang Li , Zezhong Zhang , Guangxu Zhu , Caijun Zhong

We consider a Gaussian multiple access channel with $K$ transmitters, a (intended) receiver and an external eavesdropper. The transmitters wish to reliably communicate with the receiver while concealing their messages from the eavesdropper.…

Cryptography and Security · Computer Science 2015-04-23 Parisa Babaheidarian , Somayeh Salimi

This work investigates the effect of finite-alphabet source input on the secrecy rate of a multi-antenna wiretap system. Existing works have characterized maximum achievable secrecy rate or secrecy capacity for single and multiple antenna…

Information Theory · Computer Science 2016-11-15 Shafi Bashar , Zhi Ding , Chengshan Xiao

We consider the multi-antenna wiretap channel in which the transmitter wishes to send a confidential message to its receiver while keeping it secret to the eavesdropper. It has been known that the secrecy capacity of such a channel does not…

Information Theory · Computer Science 2016-11-17 Mari Kobayashi , Pablo Piantanida , Sheng Yang , Shlomo Shamai

End-to-end training of deep learning-based models allows for implicit learning of intermediate representations based on the final task loss. However, the end-to-end approach ignores the useful domain knowledge encoded in explicit…

Computation and Language · Computer Science 2017-04-20 Shubham Toshniwal , Hao Tang , Liang Lu , Karen Livescu

Deterministic neural nets have been shown to learn effective predictors on a wide range of machine learning problems. However, as the standard approach is to train the network to minimize a prediction loss, the resultant model remains…

Machine Learning · Computer Science 2018-11-02 Murat Sensoy , Lance Kaplan , Melih Kandemir

This paper considers an information theoretic model of secure integrated sensing and communication, represented as a wiretap channel with action dependent states. This model allows securing part of a transmitted message against a sensed…

Information Theory · Computer Science 2024-09-10 Truman Welling , Onur Günlü , Aylin Yener

In this work, an explicit wiretap coding scheme based on polar lattices is proposed to achieve the secrecy capacity of the additive white Gaussian noise (AWGN) wiretap channel. Firstly, polar lattices are used to construct secrecy-good…

Information Theory · Computer Science 2017-12-27 Ling Liu , Yanfei Yan , Cong Ling

This paper studies the K-user Gaussian interference channel with secrecy constraints. Two distinct network models, namely the interference channel with confidential messages and the one with an external eavesdropper, are analyzed. Using…

Information Theory · Computer Science 2016-11-15 Onur Ozan Koyluoglu , Hesham El Gamal , Lifeng Lai , H. Vincent Poor

Previous studies have demonstrated that end-to-end learning enables significant shaping gains over additive white Gaussian noise (AWGN) channels. However, its benefits have not yet been quantified over realistic wireless channel models.…

Information Theory · Computer Science 2021-07-30 Fayçal Ait Aoudia , Jakob Hoydis

Probabilistic constellation shaping enables easy rate adaption and has been proven to reduce the gap to Shannon capacity. Constellation point probabilities are optimized to maximize either the mutual information or the bit-wise mutual…

Information Theory · Computer Science 2025-06-23 Shrinivas Chimmalgi , Laurent Schmalen , Vahid Aref

We investigate the transmission of a secret message from Alice to Bob in the presence of an eavesdropper (Eve) and many of decode-and-forward relay nodes. Each link comprises a set of parallel channels, modeling for example an orthogonal…

Information Theory · Computer Science 2018-07-18 Linda Senigagliesi , Marco Baldi , Stefano Tomasin

This paper studies implicit communication in linear quadratic Gaussian control systems. We show that the control system itself can serve as an implicit communication channel, enabling the controller to transmit messages through its inputs…

Information Theory · Computer Science 2025-11-19 Gongpu Chen , Deniz Gunduz

Modeling uncertainty in deep neural networks, despite recent important advances, is still an open problem. Bayesian neural networks are a powerful solution, where the prior over network weights is a design choice, often a normal…

Machine Learning · Statistics 2019-10-29 Raanan Y. Rohekar , Yaniv Gurwicz , Shami Nisimov , Gal Novik

We propose a new secret communication scheme over the bosonic wiretap channel. It uses readily available hardware such as lasers and direct photodetectors. The scheme is based on randomness extractors, pulse-position modulation, and…

Quantum Physics · Physics 2025-12-10 Esther Hänggi , Iyán Méndez Veiga , Ligong Wang

An upper bound to the identification capacity of discrete memoryless wiretap channels is derived under the requirement of semantic effective secrecy, combining semantic secrecy and stealth constraints. A previously established lower bound…

Information Theory · Computer Science 2023-06-27 Johannes Rosenberger , Abdalla Ibrahim , Boulat A. Bash , Christian Deppe , Roberto Ferrara , Uzi Pereg

This paper studies secrecy-capacity of an $n$-dimensional Gaussian wiretap channel under a peak-power constraint. This work determines the largest peak-power constraint $\bar{\mathsf{R}}_n$ such that an input distribution uniformly…

Information Theory · Computer Science 2023-05-17 Antonino Favano , Luca Barletta , Alex Dytso

In this paper we consider a wiretap channel with a secret key buffer. We use the coding scheme of [1] to enhance the secrecy rate to the capacity of the main channel, while storing each securely transmitted message in the secret key buffer.…

Information Theory · Computer Science 2016-07-06 Shahid Mehraj Shah , Vinod Sharma