Nicholas Carlini
Nicholas Carlini
Google Brain
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TitleCited byYear
Towards evaluating the robustness of neural networks
N Carlini, D Wagner
2017 IEEE Symposium on Security and Privacy (SP), 39-57, 2017
14052017
Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples
A Athalye, N Carlini, D Wagner
ICML 2018, 2018
5672018
Adversarial examples are not easily detected: Bypassing ten detection methods
N Carlini, D Wagner
Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security…, 2017
4362017
{ROP} is Still Dangerous: Breaking Modern Defenses
N Carlini, D Wagner
23rd {USENIX} Security Symposium ({USENIX} Security 14), 385-399, 2014
2792014
Control-flow bending: On the effectiveness of control-flow integrity
N Carlini, A Barresi, M Payer, D Wagner, TR Gross
24th {USENIX} Security Symposium ({USENIX} Security 15), 161-176, 2015
2602015
cleverhans v2. 0.0: an adversarial machine learning library
N Papernot, N Carlini, I Goodfellow, R Feinman, F Faghri, A Matyasko, ...
arXiv preprint arXiv:1610.00768, 2016
237*2016
Hidden Voice Commands.
N Carlini, P Mishra, T Vaidya, Y Zhang, M Sherr, C Shields, D Wagner, ...
USENIX Security Symposium, 513-530, 2016
2262016
Audio adversarial examples: Targeted attacks on speech-to-text
N Carlini, D Wagner
2018 IEEE Security and Privacy Workshops (SPW), 1-7, 2018
1832018
Adversarial example defense: Ensembles of weak defenses are not strong
W He, J Wei, X Chen, N Carlini, D Song
11th {USENIX} Workshop on Offensive Technologies ({WOOT} 17), 2017
1202017
Defensive distillation is not robust to adversarial examples
N Carlini, D Wagner
arXiv preprint arXiv:1607.04311, 2016
1182016
An Evaluation of the Google Chrome Extension Security Architecture.
N Carlini, AP Felt, D Wagner
USENIX Security Symposium, 97-111, 2012
1022012
The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks
N Carlini, C Liu, J Kos, Erlingsson, D Song
81*2019
Magnet and "efficient defenses against adversarial attacks" are not robust to adversarial examples
N Carlini, D Wagner
arXiv preprint arXiv:1711.08478, 2017
782017
Provably minimally-distorted adversarial examples
N Carlini, G Katz, C Barrett, DL Dill
arXiv preprint arXiv:1709.10207, 2017
56*2017
On Evaluating Adversarial Robustness
N Carlini, A Athalye, N Papernot, W Brendel, J Rauber, D Tsipras, ...
arXiv preprint arXiv:1902.06705, 2019
512019
On the Robustness of the CVPR 2018 White-Box Adversarial Example Defenses
A Athalye, N Carlini
arXiv preprint arXiv:1804.03286, 2018
492018
MixMatch: A Holistic Approach to Semi-Supervised Learning
D Berthelot, N Carlini, I Goodfellow, N Papernot, A Oliver, C Raffel
arXiv preprint arXiv:1905.02249, 2019
302019
Adversarial Examples Are a Natural Consequence of Test Error in Noise
N Ford, J Gilmer, N Carlini, D Cubuk
arXiv preprint arXiv:1901.10513, 2019
252019
Unrestricted Adversarial Examples
TB Brown, N Carlini, C Zhang, C Olsson, P Christiano, I Goodfellow
arXiv preprint arXiv:1809.08352, 2018
202018
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition
Y Qin, N Carlini, I Goodfellow, G Cottrell, C Raffel
arXiv preprint arXiv:1903.10346, 2019
152019
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