{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,12]],"date-time":"2026-05-12T03:17:51Z","timestamp":1778555871434,"version":"3.51.4"},"reference-count":32,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2019,5,28]],"date-time":"2019-05-28T00:00:00Z","timestamp":1559001600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61572114"],"award-info":[{"award-number":["61572114"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this paper, a deep learning (DL)-based physical (PHY) layer authentication framework is proposed to enhance the security of industrial wireless sensor networks (IWSNs). Three algorithms, the deep neural network (DNN)-based sensor nodes\u2019 authentication method, the convolutional neural network (CNN)-based sensor nodes\u2019 authentication method, and the convolution preprocessing neural network (CPNN)-based sensor nodes\u2019 authentication method, have been adopted to implement the PHY-layer authentication in IWSNs. Among them, the improved CPNN-based algorithm requires few computing resources and has extremely low latency, which enable a lightweight multi-node PHY-layer authentication. The adaptive moment estimation (Adam) accelerated gradient algorithm and minibatch skill are used to accelerate the training of the neural networks. Simulations are performed to evaluate the performance of each algorithm and a brief analysis of the application scenarios for each algorithm is discussed. Moreover, the experiments have been performed with universal software radio peripherals (USRPs) to evaluate the authentication performance of the proposed algorithms. Due to the trainings being performed on the edge sides, the proposed method can implement a lightweight authentication for the sensor nodes under the edge computing (EC) system in IWSNs.<\/jats:p>","DOI":"10.3390\/s19112440","type":"journal-article","created":{"date-parts":[[2019,5,28]],"date-time":"2019-05-28T11:18:09Z","timestamp":1559042289000},"page":"2440","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":91,"title":["Deep-Learning-Based Physical Layer Authentication for Industrial Wireless Sensor Networks"],"prefix":"10.3390","volume":"19","author":[{"given":"Run-Fa","family":"Liao","sequence":"first","affiliation":[{"name":"National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8645-2264","authenticated-orcid":false,"given":"Hong","family":"Wen","sequence":"additional","affiliation":[{"name":"School of Aeronautics and Astronautics, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4720-5946","authenticated-orcid":false,"given":"Jinsong","family":"Wu","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, Universidad de Chile, Santiago 8370451, Chile"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fei","family":"Pan","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Aidong","family":"Xu","sequence":"additional","affiliation":[{"name":"EPRI, China Southern Power Grid Co., Ltd., Guangzhou 510080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yixin","family":"Jiang","sequence":"additional","affiliation":[{"name":"EPRI, China Southern Power Grid Co., Ltd., Guangzhou 510080, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feiyi","family":"Xie","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Minggui","family":"Cao","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Science and Technology on Communications, University of Electronic Science and Technology of China, Chengdu 611731, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"96","DOI":"10.3390\/fi2020096","article-title":"Survey on wireless sensor network technologies for industrial automation: The security and quality of service perspectives","volume":"2","author":"Christin","year":"2010","journal-title":"Future Internet"},{"key":"ref_2","unstructured":"Low, K.S., Win, W.N.N., and Er, M.J. 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