{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T15:29:10Z","timestamp":1777390150334,"version":"3.51.4"},"reference-count":27,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2022,10,1]],"date-time":"2022-10-01T00:00:00Z","timestamp":1664582400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Natural Science Basic Research Program of Shaanxi","award":["2021JQ-207"],"award-info":[{"award-number":["2021JQ-207"]}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["XJS211506"],"award-info":[{"award-number":["XJS211506"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62002278"],"award-info":[{"award-number":["62002278"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>To ensure that unmanned aerial vehicle (UAV) positioning is not affected by GPS spoofing signals, we propose PerDet, a perception-data-based UAV GPS spoofing detection approach utilizing machine learning algorithms. Based on the principle of the position estimation process and attitude estimation process, we choose the data gathered by the accelerometer, gyroscope, magnetometer, GPS and barometer as features. Although these sensors have different shortcomings, their variety makes sure that the selected perception data can compensate for each other. We collect the experimental data through real flights, which make PerDet more practical. Furthermore, we run various machine learning algorithms on our dataset and select the most effective classifier as the detector. Through the performance evaluation and comparison, we demonstrate that PerDet is better than existing methods and is an effective method with a detecting rate of 99.69%. For a fair comparison, we reproduce the existing method and run it on our dataset to compare the performance between this method and our PerDet approach.<\/jats:p>","DOI":"10.3390\/rs14194925","type":"journal-article","created":{"date-parts":[[2022,10,10]],"date-time":"2022-10-10T03:07:28Z","timestamp":1665371248000},"page":"4925","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":44,"title":["PerDet: Machine-Learning-Based UAV GPS Spoofing Detection Using Perception Data"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2658-1694","authenticated-orcid":false,"given":"Xiaomin","family":"Wei","sequence":"first","affiliation":[{"name":"School of Cyber Engineering, Xidian University, Xi\u2019an 710071, China"},{"name":"ISN State Key Laboratory, Xidian University, Xi\u2019an 710071, China"},{"name":"Shaanxi Key Laboratory of Network and System Security, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yao","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Cyber Engineering, Xidian University, Xi\u2019an 710071, China"},{"name":"ISN State Key Laboratory, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cong","family":"Sun","sequence":"additional","affiliation":[{"name":"School of Cyber Engineering, Xidian University, Xi\u2019an 710071, China"},{"name":"ISN State Key Laboratory, Xidian University, Xi\u2019an 710071, China"},{"name":"Shaanxi Key Laboratory of Network and System Security, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,10,1]]},"reference":[{"key":"ref_1","unstructured":"Humphreys, T. 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Proceedings of the 2014 Science and Information Conference, London, UK.","DOI":"10.1109\/SAI.2014.6918213"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/19\/4925\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T00:45:23Z","timestamp":1760143523000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/19\/4925"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,10,1]]},"references-count":27,"journal-issue":{"issue":"19","published-online":{"date-parts":[[2022,10]]}},"alternative-id":["rs14194925"],"URL":"https:\/\/doi.org\/10.3390\/rs14194925","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,10,1]]}}}