An ADS‐B signal poisoning method based on generative adversarial network
نویسندگان
چکیده
Automatic dependent surveillance-broadcast (ADS-B) has been widely used due to its low cost and high precision. The deep learning methods for ADS-B signal classification have achieved a performance. However, recent studies shown that networks are very sensitive vulnerable small noise. An poisoning method based on Generative Adversarial Network is proposed. This can generate poisoned signals. One of assigned as the attacked network another one protected network. When signals fed into these two well-performed networks, will be recognized incorrectly by while classified correctly attack-protect-similar loss function further proposed achieve ‘triple-win’ in leading poor performance, well performance similar unpoisoned Experimental results show classifies with 1.55% accuracy, rate still maintained at 99.38%.
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ژورنال
عنوان ژورنال: Electronics Letters
سال: 2023
ISSN: ['0013-5194', '1350-911X']
DOI: https://doi.org/10.1049/ell2.12699