Numerical results show that a priori approach shows better performance thanks to the additional learning steps of the legitimate receiver while a posteriori possesses practical strength since it can be applied to any fixed receivers not requiring any additional learning steps.
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Semantic Scholar extracted view of "Secure wireless communication via adversarial machine learning: A Priori vs. A Posteriori" by Ju-yeol Seo et al.
To this end, we propose two design approaches of the adversarial examples: (i) A priori; (ii) A posteriori, i.e. before and after learning steps of the receiver ...
Secure wireless communication via adversarial machine learning: A Priori vs. A Posteriori. Secure wireless communication via adversarial machine learning: A ...
Secure wireless communication via adversarial machine learning: A ...
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Secure wireless communication via adversarial machine learning: A Priori vs. A Posteriori. This paper considers wireless communication system consisted of ...
Secure wireless communication via adversarial machine learning: A Priori vs. A Posteriori. Secure wireless communication via adversarial machine learning: A ...
Secure wireless communication via adversarial machine learning: A Priori vs. ... A posteriori, i.e. before and after learning steps of the receiver, respectively.
Secure wireless communication via adversarial machine learning: A Priori vs. A Posteriori · Computer Science. ICT Express · 2022.
Mar 13, 2023 · Abstract—Data-driven machine learning (ML) is promoted as one potential technology to be used in next-generations wireless systems.
We consider adversarial machine learning settings in wireless communication systems with adversaries that attempt to manipulate the deep learning (DL)-based ...
Missing: Secure Priori Posteriori.