{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,22]],"date-time":"2025-12-22T04:33:42Z","timestamp":1766378022286,"version":"3.37.3"},"reference-count":28,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"vor","delay-in-days":1,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Educational scientific research project of Fujian Provincial Department of Education"},{"name":"the Key Laboratory of PK System Technologies Research of Hainan","award":["JAT210291","25622114"],"award-info":[{"award-number":["JAT210291","25622114"]}]},{"DOI":"10.13039\/100000001","name":"NSF","doi-asserted-by":"publisher","award":["62172095","61732010","61872234"],"award-info":[{"award-number":["62172095","61732010","61872234"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,11,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>With the rapid development of the Internet of Things (IoT), network security challenges are becoming more and more complex, and the scale of intrusion attacks against the network is gradually increasing. Therefore, researchers have proposed Intrusion Detection Systems and constantly designed more effective systems to defend against attacks. One issue to consider is using limited computing power to process complex network data efficiently. In this paper, we take the AWID dataset as an example, propose an efficient data processing method to mitigate the interference caused by redundant data and design a lightweight deep learning-based model to analyze and predict the data category. Finally, we achieve an overall accuracy of 99.77% and an accuracy of 97.95% for attacks on the AWID dataset, with a detection rate of 99.98% for the injection attack. Our model has low computational overhead and a fast response time after training, ensuring the feasibility of applying to edge nodes with weak computational power in the IoT.<\/jats:p>","DOI":"10.1093\/comjnl\/bxac119","type":"journal-article","created":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T05:46:01Z","timestamp":1664603161000},"page":"2870-2879","source":"Crossref","is-referenced-by-count":13,"title":["An Efficient Deep Learning Approach To IoT Intrusion Detection"],"prefix":"10.1093","volume":"65","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5623-5955","authenticated-orcid":false,"given":"Jin","family":"Cao","sequence":"first","affiliation":[{"name":"Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering, , Shanghai 200240 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2228-502X","authenticated-orcid":false,"given":"Liwei","family":"Lin","sequence":"additional","affiliation":[{"name":"FuJian University of Technology School of Computer Science and Mathematics, , Fuzhou, Fujian 350028 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9592-8490","authenticated-orcid":false,"given":"Ruhui","family":"Ma","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering, , Shanghai 200240 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4714-7400","authenticated-orcid":false,"given":"Haibing","family":"Guan","sequence":"additional","affiliation":[{"name":"Shanghai Jiao Tong University School of Electronic Information and Electrical Engineering, , Shanghai 200240 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4849-5535","authenticated-orcid":false,"given":"Mengke","family":"Tian","sequence":"additional","affiliation":[{"name":"Peking University School of Integrated Circuits, , Beijing 100871 , China"},{"name":"Beijing Microelectronics Technology Institute , Beijing 100076 , China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5905-3022","authenticated-orcid":false,"given":"Yong","family":"Wang","sequence":"additional","affiliation":[{"name":"Beijing Microelectronics Technology Institute , Beijing 100076 , China"}]}],"member":"286","published-online":{"date-parts":[[2022,9,30]]},"reference":[{"key":"2023093003004810500_ref1","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1007\/s10796-014-9492-7","article-title":"The internet of things: a survey","volume":"17","author":"Li","year":"2015","journal-title":"Inf. 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