Semantic Entropy Can Simultaneously Benefit Transmission Efficiency and Channel Security of Wireless Semantic Communications

Fuente: arXiv
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Main Authors: Rong, Yankai, Nan, Guoshun, Zhang, Minwei, Chen, Sihan, Wang, Songtao, Zhang, Xuefei, Ma, Nan, Gong, Shixun, Yang, Zhaohui, Cui, Qimei, Tao, Xiaofeng, Quek, Tony Q. S.
Format: Preprint
Published: 2024
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author Rong, Yankai
Nan, Guoshun
Zhang, Minwei
Chen, Sihan
Wang, Songtao
Zhang, Xuefei
Ma, Nan
Gong, Shixun
Yang, Zhaohui
Cui, Qimei
Tao, Xiaofeng
Quek, Tony Q. S.
author_facet Rong, Yankai
Nan, Guoshun
Zhang, Minwei
Chen, Sihan
Wang, Songtao
Zhang, Xuefei
Ma, Nan
Gong, Shixun
Yang, Zhaohui
Cui, Qimei
Tao, Xiaofeng
Quek, Tony Q. S.
contents Recently proliferated deep learning-based semantic communications (DLSC) focus on how transmitted symbols efficiently convey a desired meaning to the destination. However, the sensitivity of neural models and the openness of wireless channels cause the DLSC system to be extremely fragile to various malicious attacks. This inspires us to ask a question: "Can we further exploit the advantages of transmission efficiency in wireless semantic communications while also alleviating its security disadvantages?". Keeping this in mind, we propose SemEntropy, a novel method that answers the above question by exploring the semantics of data for both adaptive transmission and physical layer encryption. Specifically, we first introduce semantic entropy, which indicates the expectation of various semantic scores regarding the transmission goal of the DLSC. Equipped with such semantic entropy, we can dynamically assign informative semantics to Orthogonal Frequency Division Multiplexing (OFDM) subcarriers with better channel conditions in a fine-grained manner. We also use the entropy to guide semantic key generation to safeguard communications over open wireless channels. By doing so, both transmission efficiency and channel security can be simultaneously improved. Extensive experiments over various benchmarks show the effectiveness of the proposed SemEntropy. We discuss the reason why our proposed method benefits secure transmission of DLSC, and also give some interesting findings, e.g., SemEntropy can keep the semantic accuracy remain 95% with 60% less transmission.
format Preprint
id arxiv_https___arxiv_org_abs_2402_02950
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Semantic Entropy Can Simultaneously Benefit Transmission Efficiency and Channel Security of Wireless Semantic Communications
Rong, Yankai
Nan, Guoshun
Zhang, Minwei
Chen, Sihan
Wang, Songtao
Zhang, Xuefei
Ma, Nan
Gong, Shixun
Yang, Zhaohui
Cui, Qimei
Tao, Xiaofeng
Quek, Tony Q. S.
Cryptography and Security
Signal Processing
Recently proliferated deep learning-based semantic communications (DLSC) focus on how transmitted symbols efficiently convey a desired meaning to the destination. However, the sensitivity of neural models and the openness of wireless channels cause the DLSC system to be extremely fragile to various malicious attacks. This inspires us to ask a question: "Can we further exploit the advantages of transmission efficiency in wireless semantic communications while also alleviating its security disadvantages?". Keeping this in mind, we propose SemEntropy, a novel method that answers the above question by exploring the semantics of data for both adaptive transmission and physical layer encryption. Specifically, we first introduce semantic entropy, which indicates the expectation of various semantic scores regarding the transmission goal of the DLSC. Equipped with such semantic entropy, we can dynamically assign informative semantics to Orthogonal Frequency Division Multiplexing (OFDM) subcarriers with better channel conditions in a fine-grained manner. We also use the entropy to guide semantic key generation to safeguard communications over open wireless channels. By doing so, both transmission efficiency and channel security can be simultaneously improved. Extensive experiments over various benchmarks show the effectiveness of the proposed SemEntropy. We discuss the reason why our proposed method benefits secure transmission of DLSC, and also give some interesting findings, e.g., SemEntropy can keep the semantic accuracy remain 95% with 60% less transmission.
title Semantic Entropy Can Simultaneously Benefit Transmission Efficiency and Channel Security of Wireless Semantic Communications
topic Cryptography and Security
Signal Processing
url https://arxiv.org/abs/2402.02950