Defending against adversarial attacks in deep neural networks

Suya You; C-C Jay Kuo

doi:10.1117/12.2519268

10 May 2019 Defending against adversarial attacks in deep neural networks

Suya You, C-C Jay Kuo

Proceedings Volume 11006, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications; 110061C (2019) https://doi.org/10.1117/12.2519268
Event: SPIE Defense + Commercial Sensing, 2019, Baltimore, MD, United States

Abstract

We focus on defending against adversarial attacks in deep neural networks using signal analysis technology. The method employs a novel signal processing theory as a defense to adversarial perturbations. The method neither modifies the protected network nor requires knowledge of the process for generating adversarial examples. Extensive evaluation experiments demonstrate the efficiency and effectiveness of the proposed adversarial defending method.

Conference Presentation

Citation Download Citation

Suya You and C-C Jay Kuo "Defending against adversarial attacks in deep neural networks", Proc. SPIE 11006, Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications, 110061C (10 May 2019); https://doi.org/10.1117/12.2519268

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