Towards Adversarial and Unintentional Collisions Detection Using Deep Learning

Hai N. Nguyen,Tien Vo-Huu,Triet Vo-Huu,Guevara Noubir

Proceedings of the ACM Workshop on Wireless Security and Machine Learning（2019）

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摘要

We introduce a set of techniques to achieve transfer learning from computer vision to RF spectrum analysis. In this paper, we demonstrate the usefulness of this approach to scale the learning, accuracy, and efficiency of detection of adversarial and unintentional communications collisions using VGG-16. We achieve high accuracy (94% collisions detected) on a DARPA Spectrum Collaboration Challenge (SC2) dataset.

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关键词

Convolutional neural networks, transfer learning, wireless collision detection

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