Investigating the significance of adversarial attacks and their relation to interpretability for radar-based human activity recognition systems

Author:

Ozbulak Utku,Vandersmissen Baptist,Jalalvand Azarakhsh,Couckuyt Ivo,Van Messem Arnout,De Neve Wesley

Funder

Ghent University Global Campus, Republic of Korea

Ghent University, Belgium

imec, Belgium

Flanders Innovation & Entrepreneurship (VLAIO), Belgium

Scientific Research-Flanders (FWO-Flanders), Belgium

EU

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing,Software

Reference56 articles.

1. Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples;Athalye,2018

2. Evasion attacks against machine learning at test time;Biggio,2013

3. Adversarial patch;Brown,2017

4. Towards evaluating the robustness of neural networks;Carlini,2016

5. Adversarial examples are not easily detected: Bypassing ten detection methods;Carlini,2017

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