{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T16:26:29Z","timestamp":1781195189985,"version":"3.54.1"},"reference-count":27,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T00:00:00Z","timestamp":1648512000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>A Global Positioning System (GPS) spoofing attack can be launched against any commercial GPS sensor in order to interfere with its navigation capabilities. These sensors are installed in a variety of devices and vehicles (e.g., cars, planes, cell phones, ships, UAVs, and more). In this study, we focus on micro UAVs (drones) for several reasons: (1) they are small and inexpensive, (2) they rely on a built-in camera, (3) they use GPS sensors, and (4) it is difficult to add external components to micro UAVs. We propose an innovative method, based on the video stream captured by a drone\u2019s camera, for the real-time detection of GPS spoofing attacks targeting drones. The proposed method collects frames from the video stream and their location (GPS coordinates); by calculating the correlation between each frame, our method can detect GPS spoofing attacks on drones. We first analyze the performance of the suggested method in a controlled environment by conducting experiments on a flight simulator that we developed. Then, we analyze its performance in the real world using a DJI drone. Our method can provide different levels of security against GPS spoofing attacks, depending on the detection interval required; for example, it can provide a high level of security to a drone flying at altitudes of 50\u2013100 m over an urban area at an average speed of 4 km\/h in conditions of low ambient light; in this scenario, the proposed method can provide a level of security that detects any GPS spoofing attack in which the spoofed location is a distance of 1\u20134 m (an average of 2.5 m) from the real location.<\/jats:p>","DOI":"10.3390\/s22072608","type":"journal-article","created":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T21:45:51Z","timestamp":1648590351000},"page":"2608","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["Towards the Detection of GPS Spoofing Attacks against Drones by Analyzing Camera\u2019s Video Stream"],"prefix":"10.3390","volume":"22","author":[{"given":"Barak","family":"Davidovich","sequence":"first","affiliation":[{"name":"Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3453-2120","authenticated-orcid":false,"given":"Ben","family":"Nassi","sequence":"additional","affiliation":[{"name":"Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9641-128X","authenticated-orcid":false,"given":"Yuval","family":"Elovici","sequence":"additional","affiliation":[{"name":"Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva 8410501, Israel"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Nassi, B., Bitton, R., Masuoka, R., Shabtai, A., and Elovici, Y. (2021, January 24\u201327). SoK: Security and privacy in the age of commercial drones. Proceedings of the 2021 IEEE Symposium on Security and Privacy (SP), San Francisco, CA, USA.","DOI":"10.1109\/SP40001.2021.00005"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Abera, T., Bahmani, R., Brasser, F., Ibrahim, A., Sadeghi, A.R., and Schunter, M. (2019, January 24\u201327). DIAT: Data Integrity Attestation for Resilient Collaboration of Autonomous Systems. Proceedings of the NDSS Symposium, San Diego, CA, USA.","DOI":"10.14722\/ndss.2019.23420"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Jansen, K., Tippenhauer, N.O., and P\u00f6pper, C. (2016, January 5\u20139). Multi-receiver GPS spoofing detection: Error models and realization. Proceedings of the 32nd Annual Conference on Computer Security Applications, Los Angeles, CA, USA.","DOI":"10.1145\/2991079.2991092"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Ranganathan, A., \u00d3lafsd\u00f3ttir, H., and Capkun, S. (2016, January 3\u20137). Spree: A spoofing resistant gps receiver. Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking, New York, NY, USA.","DOI":"10.1145\/2973750.2973753"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Xue, N., Niu, L., Hong, X., Li, Z., Hoffaeller, L., and P\u00f6pper, C. (2020, January 7\u201311). DeepSIM: GPS Spoofing Detection on UAVs using Satellite Imagery Matching. Proceedings of the Annual Computer Security Applications Conference, Austin, TX, USA.","DOI":"10.1145\/3427228.3427254"},{"key":"ref_6","unstructured":"Davidovich, B. (2022, February 23). Github. Available online: https:\/\/github.com\/davbarak\/VISAS."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Ferreira, R., Gaspar, J., Sebasti\u00e3o, P., and Souto, N. (2022). A Software Defined Radio Based Anti-UAV Mobile System with Jamming and Spoofing Capabilities. Sensors, 22.","DOI":"10.3390\/s22041487"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1002\/rob.21513","article-title":"Unmanned aircraft capture and control via GPS spoofing","volume":"31","author":"Kerns","year":"2014","journal-title":"J. Field Robot."},{"key":"ref_9","unstructured":"Luo, A. (2016, January 4\u20137). Drones hijacking\u2014multi-dimensional attack vectors and countermeasures. Proceedings of the DEF CON 24 Conference, Las Vegas, NV, USA. Available online: https:\/\/www.youtube.com\/watch?v=R6RZ5KqSVcg."},{"key":"ref_10","unstructured":"Zeng, K.C., Liu, S., Shu, Y., Wang, D., Li, H., Dou, Y., Wang, G., and Yang, Y. (2018, January 15\u201317). All your {GPS} are belong to us: Towards stealthy manipulation of road navigation systems. Proceedings of the 27th USENIX Security Symposium (USENIX Security 18), Baltimore, MD, USA. Available online: https:\/\/www.usenix.org\/conference\/usenixsecurity18\/presentation\/zeng."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Oligeri, G., Sciancalepore, S., and Di Pietro, R. (2020, January 8\u201310). GNSS spoofing detection via opportunistic IRIDIUM signals. Proceedings of the 13th ACM Conference on Security and Privacy in Wireless and Mobile Networks, Linz, Austria.","DOI":"10.1145\/3395351.3399350"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Sathaye, H., LaMountain, G., Closas, P., and Ranganathan, A. (2022, February 23). SemperFi: Anti-Spoofing GPS Receiver for UAVs. Available online: https:\/\/harshadsathaye.com\/files\/semperfi_ndss22.pdf.","DOI":"10.14722\/ndss.2022.23071"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Eichelberger, M., Von Hagen, F., and Wattenhofer, R. (2020, January 21\u201324). A Spoof-Proof GPS Receiver. Proceedings of the 2020 19th ACM\/IEEE International Conference on Information Processing in Sensor Networks (IPSN), Sydney, Australia.","DOI":"10.1109\/IPSN48710.2020.00-39"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Oligeri, G., Sciancalepore, S., Ibrahim, O.A., and Di Pietro, R. (2019, January 15\u201317). Drive me not: GPS spoofing detection via cellular network: (Architectures, models, and experiments). Proceedings of the 12th Conference on Security and Privacy in Wireless and Mobile Networks, Miami, FL, USA.","DOI":"10.1145\/3317549.3319719"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Dang, Y., Benza\u00efd, C., Shen, Y., and Taleb, T. (2020, January 7\u201311). GPS spoofing detector with adaptive trustable residence area for cellular based-UAVs. Proceedings of the GLOBECOM 2020\u20142020 IEEE Global Communications Conference, Taipei, Taiwan.","DOI":"10.1109\/GLOBECOM42002.2020.9348030"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3229","DOI":"10.1109\/TCOMM.2020.2973629","article-title":"Mobility in the sky: Performance and mobility analysis for cellular-connected UAVs","volume":"68","author":"Amer","year":"2020","journal-title":"IEEE Trans. Commun."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Wang, C.C., Chen, J.C., Chen, Y., Tu, R.H., Lee, J.J., Xiao, Y.X., and Cai, S.Y. (2021, January 25\u201329). MVP: Magnetic vehicular positioning system for GNSS-denied environments. Proceedings of the 27th Annual International Conference on Mobile Computing and Networking, New Orleans, LA, USA.","DOI":"10.1145\/3447993.3483264"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3289390","article-title":"An Efficient UAV Hijacking Detection Method Using Onboard Inertial Measurement Unit","volume":"17","author":"Feng","year":"2018","journal-title":"ACM Trans. Embed. Comput. Syst. (TECS)"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Qiao, Y., Zhang, Y., and Du, X. (2017, January 15\u201318). A Vision-Based GPS-Spoofing Detection Method for Small UAVs. Proceedings of the 2017 13th International Conference on Computational Intelligence and Security (CIS), Hong Kong, China.","DOI":"10.1109\/CIS.2017.00074"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Kwon, K.C., and Shim, D.S. (2020). Performance analysis of direct gps spoofing detection method with ahrs\/accelerometer. Sensors, 20.","DOI":"10.3390\/s20040954"},{"key":"ref_21","unstructured":"Wikipedia (2022, February 23). Technology Readiness Level\u2014Wikipedia, The Free Encyclopedia. Available online: http:\/\/en.wikipedia.org\/w\/index.php?title=Technology%20readiness%20level&oldid=1060145453."},{"key":"ref_22","unstructured":"(2022, February 23). Feature Matching. Available online: https:\/\/docs.opencv.org\/4.x\/dc\/dc3\/tutorial_py_matcher.html."},{"key":"ref_23","unstructured":"(2022, February 23). Introduction to Surf (Speeded-Up Robust Features). Available online: https:\/\/docs.opencv.org\/3.4\/df\/dd2\/tutorial_py_surf_intro.html."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Jakubovi\u0107, A., and Velagi\u0107, J. (2018, January 16\u201319). Image feature matching and object detection using brute-force matchers. Proceedings of the 2018 International Symposium ELMAR, Zadar, Croatia.","DOI":"10.23919\/ELMAR.2018.8534641"},{"key":"ref_25","unstructured":"Google (2022, February 23). Google Earth. Available online: https:\/\/www.google.com\/earth\/."},{"key":"ref_26","unstructured":"Dey, S. (2018). Hands-On Image Processing with Python: Expert Techniques for Advanced Image Analysis and Effective Interpretation of Image Data, Packt Publishing Ltd."},{"key":"ref_27","unstructured":"DJI (2022, February 23). Dji SDK Platform. Available online: https:\/\/developer.dji.com\/."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/7\/2608\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:45:34Z","timestamp":1760136334000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/7\/2608"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,29]]},"references-count":27,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["s22072608"],"URL":"https:\/\/doi.org\/10.3390\/s22072608","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,29]]}}}