面向资源受限电力物联网终端的语义安全通信方法

杨会峰; 尚立; 崔俊彬; 刘红艳; 王九成; 蔺鹏

doi:10.11959/j.issn.2096-3750.2025.00455

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面向资源受限电力物联网终端的语义安全通信方法

能源物联网 | 更新时间：2025-07-29

- 面向资源受限电力物联网终端的语义安全通信方法
- A semantic secure communication approach for resource-constrained power IoT terminals
- 物联网学报 2025年9卷第2期页码：107-116
- 作者机构：
  
  1.国网河北省电力有限公司信息通信分公司，河北石家庄 050051
  2.北京万可信息技术有限公司，北京 100085
- 作者简介：
  
  [ "杨会峰（1973– ），男，国网河北省电力有限公司信息通信分公司副总经理、高级工程师，主要研究方向为通信传输网络、交换网络、智能电网等。" ]
  [ "尚立（1982– ），男，国网河北省电力有限公司信息通信分公司高级工程师，主要研究方向为数据传输网络、应急通信等。" ]
  [ "崔俊彬（1989– ），男，国网河北省电力有限公司信息通信分公司工程师，主要研究方向为数据传输网络、交换网络等。" ]
  [ "刘红艳（1989– ），女，国网河北省电力有限公司信息通信分公司工程师，主要研究方向为交换网络、数据通信网等。" ]
  [ "王九成（1993– ），男，国网河北省电力有限公司信息通信分公司工程师，主要研究方向为数据通信网络、应急通信等。" ]
  [ "蔺鹏（1987– ），男，北京万可信息技术有限公司总经理、工程师，主要研究方向为5G/6G 网络管理与优化、网络智能管控、数据网络安全、智能电网通信网等。" ]
- 基金信息：
  
  国网河北省电力有限公司科技项目(SGHEXT00GCJS2310140)
- DOI：10.11959/j.issn.2096-3750.2025.00455
  中图分类号： TN919.8
- 收稿日期：2024-10-08，
  
  修回日期：2024-12-09，
  
  纸质出版日期：2025-06-10
- 稿件说明：
移动端阅览
杨会峰,尚立,崔俊彬等.面向资源受限电力物联网终端的语义安全通信方法[J].物联网学报,2025,09(02):107-116.

YANG Huifeng,SHANG Li,CUI Junbin,et al.A semantic secure communication approach for resource-constrained power IoT terminals[J].Chinese Journal on Internet of Things,2025,09(02):107-116.
杨会峰,尚立,崔俊彬等.面向资源受限电力物联网终端的语义安全通信方法[J].物联网学报,2025,09(02):107-116. DOI： 10.11959/j.issn.2096-3750.2025.00455.

YANG Huifeng,SHANG Li,CUI Junbin,et al.A semantic secure communication approach for resource-constrained power IoT terminals[J].Chinese Journal on Internet of Things,2025,09(02):107-116. DOI： 10.11959/j.issn.2096-3750.2025.00455.

摘要

语义模型训练通常需要耗费大量能量和时间，阻碍了在资源受限的电力物联网终端上实施语义传输。为减轻终端的能耗和时耗，建立了一种新的语义通信架构。首先，将待传数据上传至机器学习即服务（MLaaS

machine learning as a service）平台；然后，在MLaaS平台完成语义模型训练并将模型参数回传给终端；最后，通过终端进行语义推理。然而，该架构存在MLaaS平台泄露语义模型参数导致语义信息被窃听的问题。因此，进一步设计了基于特征混淆的抗窃听方法以解决语义推理阶段的MLaaS平台安全通信问题。实验结果表明，所提方法在面对被动窃听者时是有效的，能够在保证合法终端图像恢复质量的同时，显著降低窃听者恢复图像的成功率。此外，还初步验证了特征混淆模块在终端上的计算开销和时延，结果显示该方法在资源受限的电力物联网终端上具有实际应用可行性。

Abstract

The training of semantic models typically consumes a large amount of energy and time

which hinders the implementation of semantic transmission on power Internet of things (IoT) terminals with limited resources. To reduce the energy and time consumption at the terminal

a novel semantic communication architecture was proposed. Firstly

the data to be transmitted was uploaded to a machine learning as a service (MLaaS) platform. Then

the semantic model training was performed on the MLaaS platform

and the model parameters were sent back to the terminal. Finally

semantic reasoning was carried out through the terminal. However

this architecture faces the risk of the MLaaS platform leaking semantic model parameters

leading to the potential eavesdropping of semantic information. Therefore

an anti-eavesdropping method based on feature obfuscation was designed to address the security communication issue of the MLaaS platform during the semantic inference phase. Experimental results show that the proposed method is effective against passive eavesdroppers. The effectiveness of the proposed anti-eavesdropping method was demonstrated. Additionally

the computational overhead and latency of the data obfuscation module on terminals have been preliminarily verified

showing that the method is feasible for practical application on resource-constrained power IoT terminals.

关键词

Keywords

references

WANG C X , YOU X H , GAO X Q , et al . On the road to 6G: visions, requirements, key technologies, and testbeds [J ] . IEEE Communications Surveys & Tutorials , 2023 , 25 ( 2 ): 905 - 974 .

MAHMOOD N H , BERARDINELLI G , KHATIB E J , et al . A functional architecture for 6G special-purpose industrial IoT networks [J ] . IEEE Transactions on Industrial Informatics , 2023 , 19 ( 3 ): 2530 - 2540 .

LI L L . A survey on intelligence-endogenous network: architecture and technologies for future 6G [J ] . Intelligent and Converged Networks , 2024 , 5 ( 1 ): 53 - 67 .

FERRAG M A , FRIHA O , KANTARCI B , et al . Edge learning for 6G-enabled Internet of Things: a comprehensive survey of vulnerabilities, datasets, and defenses [J ] . IEEE Communications Surveys & Tutorials , 2023 , 25 ( 4 ): 2654 - 2713 .

秦志金 , 赵菼菼 , 李凡 , 等 . 多模态语义通信研究综述 [J ] . 通信学报 , 2023 , 44 ( 5 ): 28 - 41 .

QIN Z J , ZHAO T T , LI F , et al . Survey of research on multimodal semantic communication [J ] . Journal on Communications , 2023 , 44 ( 5 ): 28 - 41 .

HUANG D L , GAO F F , TAO X M , et al . Toward semantic communications: deep learning-based image semantic coding [J ] . IEEE Journal on Selected Areas in Communications , 2023 , 41 ( 1 ): 55 - 71 .

YANG W T , DU H Y , LIEW Z Q , et al . Semantic communications for future Internet: fundamentals, applications, and challenges [J ] . IEEE Communications Surveys & Tutorials , 2023 , 25 ( 1 ): 213 - 250 .

HU Q Y , ZHANG G Y , QIN Z J , et al . Robust semantic communications with masked VQ-VAE enabled codebook [J ] . IEEE Transactions on Wireless Communications , 2023 , 22 ( 12 ): 8707 - 8722 .

张平 , 牛凯 , 姚圣时 , 等 . 面向未来的语义通信: 基本原理与实现方法 [J ] . 通信学报 , 2023 , 44 ( 5 ): 1 - 14 .

ZHANG P , NIU K , YAO S S , et al . Semantic communications for future: basic principle and implementation methodology [J ] . Journal on Communications , 2023 , 44 ( 5 ): 1 - 14 .

王碧舳 , 罗倩雯 , 卞志强 , 等 . 面向6G的语义通信系统 [J ] . 移动通信 , 2023 , 47 ( 4 ): 2 - 6 .

WANG B Z , LUO Q W , BIAN Z Q , et al . A semantic communication system for 6G networks [J ] . Mobile Communications , 2023 , 47 ( 4 ): 2 - 6 .

XIE H Q , QIN Z J , LI G Y , et al . Deep learning based semantic communications: an initial investigation [C ] // GLOBECOM 2020-2020 IEEE Global Communications Conference . Piscataway : IEEE Press , 2020 : 1 - 6 .

XIE H Q , QIN Z J . A lite distributed semantic communication system for Internet of Things [J ] . IEEE Journal on Selected Areas in Communications , 2021 , 39 ( 1 ): 142 - 153 .

HUANG C Y , WANG J Z , CHEN H X , et al . zkMLaaS: a verifiable scheme for machine learning as a service [C ] // Proceedings of the GLOBECOM 2022 - 2022 IEEE Global Communications Conference . Piscataway : IEEE Press , 2022 : 5475 - 5480 .

FARSAD N , RAO M , GOLDSMITH A . Deep learning for joint source-channel coding of text [C ] // Proceedings of the 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . Piscataway : IEEE Press , 2018 : 2326 - 2330 .

BOURTSOULATZE E , BURTH KURKA D , GÜNDÜZ D . Deep joint source-channel coding for wireless image transmission [J ] . IEEE Transactions on Cognitive Communications and Networking , 2019 , 5 ( 3 ): 567 - 579 .

WANG S X , YANG K , DAI J C , et al . Distributed image transmission using deep joint source-channel coding [C ] // Proceedings of the ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . Piscataway : IEEE Press , 2022 : 5208 - 5212 .

XU J L , AI B , CHEN W , et al . Wireless image transmission using deep source channel coding with attention modules [J ] . IEEE Transactions on Circuits and Systems for Video Technology , 2022 , 32 ( 4 ): 2315 - 2328 .

WU H T , SHAO Y L , MIKOLAJCZYK K , et al . Channel-adaptive wireless image transmission with OFDM [J ] . IEEE Wireless Communications Letters , 2022 , 11 ( 11 ): 2400 - 2404 .

TUNG T Y , GÜNDÜZ D . DeepWiVe: deep-learning-aided wireless video transmission [J ] . IEEE Journal on Selected Areas in Communications , 2022 , 40 ( 9 ): 2570 - 2583 .

ZHANG W Y , BAI K Y , ZEADALLY S , et al . DeepMA: end-to-end deep multiple access for wireless image transmission in semantic communication [J ] . IEEE Transactions on Cognitive Communications and Networking , 2024 , 10 ( 2 ): 387 - 402 .

DAI J X , FAN H , ZHAO Z X , et al . Secure resource allocation for integrated sensing and semantic communication system [C ] // Proceedings of the 2024 IEEE International Conference on Communications Workshops (ICC Workshops) . Piscataway : IEEE Press , 2024 : 1225 - 1230 .

谷勇浩 , 郭振洋 , 刘威歆 . 匿名化隐私保护技术性能评估方法研究 [J ] . 信息安全研究 , 2019 , 5 ( 4 ): 293 - 297 .

GU Y H , GUO Z Y , LIU W X . Research on performance evaluation method of anonymization privacy preservation technologies [J ] . Journal of Information Security Research , 2019 , 5 ( 4 ): 293 - 297 .

ABADI M , CHU A , GOODFELLOW I , et al . Deep learning with differential privacy [C ] // Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security . New York : ACM Press , 2016 : 308 - 318 .

CHEN Y H , YANG Q Q , SHI Z G , et al . The model inversion eavesdropping attack in semantic communication systems [C ] // Proceedings of the GLOBECOM 2023-2023 IEEE Global Communications Conference . Piscataway : IEEE Press , 2023 : 5171 - 5177 .

YANG K , WANG S X , DAI J C , et al . SwinJSCC: taming swin transformer for deep joint source-channel coding [J ] . IEEE Transactions on Cognitive Communications and Networking , 2025 , 11 ( 1 ): 90 - 104 .

YANG K , WANG S X , DAI J C , et al . WITT: a wireless image transmission transformer for semantic communications [C ] // Proceedings of the ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . Piscataway : IEEE Press , 2023 : 1 - 5 .

NGUYEN L X , KIM K , LIN TUN Y , et al . Optimizing multi-user semantic communication via transfer learning and knowledge distillation [J ] . IEEE Communications Letters , 2025 , 29 ( 1 ): 90 - 94 .

YU L , WU S Y , GABBOUJ M . Multi-swin transformer based spatio-temporal information exploration for compressed video quality enhancement [J ] . IEEE Signal Processing Letters , 2024 , 31 : 1880 - 1884 .

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智能网联环境下面向语义通信的资源分配

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