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Neural networks are powering the deployment of embedded devices and Internet of Things.
Program checking
M. Blum · 1991
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Decision boundary feature extraction for neural networks
C. Lee and D. A. Landgrebe · 1997
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Watermarking, tamper-proofing, and obfuscation - tools for software protection
C. S. Collberg and C. Thomborson · 2002
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Reverse engineering state machines by interactive grammar inference
N. Walkinshaw, K. Bogdanov, M. Holcombe, and S. Salahuddin · 2007
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Principles of remote attestation
G. Coker, J. Guttman, P. Loscocco, A. Herzog, J. Millen, B. O’Hanlon, J. Ramsdell, A. Segall, J. Sheehy, and B. Sniffen · 2011
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Intriguing properties of neural networks
C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. J. Goodfellow, and R. Fergus · 2013
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Explaining and harnessing adversarial examples
I. J. Goodfellow, J. Shlens, and C. Szegedy · 2015
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2015
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Deep face recognition
O. M. Parkhi, A. Vedaldi, and A. Zisserman · 2015
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Deepx: A software accelerator for low-power deep learning inference on mobile devices
N. D. Lane, S. Bhattacharya, P. Georgiev, C. Forlivesi, L. Jiao, L. Qendro, and F. Kawsar · 2016
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Distillation as a defense to adversarial perturbations against deep neural networks
N. Papernot, P. McDaniel, X. Wu, S. Jha, and A. Swami · 2016
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Towards the science of security and privacy in machine learning
N. Papernot, P. D. McDaniel, A. Sinha, and M. P. Wellman · 2016
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Stealing machine learning models via prediction apis
F. Tramer, F. Zhang, A. Juels, M. K. Reiter, and T. Ristenpart · 2016
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Mobilenets: Efficient convolutional neural networks for mobile vision applications
A. G. Howard, M. Zhu, B. Chen, D. Kalenichenko, W. Wang, T. Weyand, M. Andreetto, and H. Adam · 2017
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Densely connected convolutional networks
G. Huang, Z. Liu, L. v. d. Maaten, and K. Q. Weinberger · 2017
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Toward an intrusion detection approach for iot based on radio communications profiling
J. Roux, E. Alata, G. Auriol, V. Nicomette, and M. Kâaniche · 2017
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Membership inference attacks against machine learning models
R. Shokri, M. Stronati, C. Song, and V. Shmatikov · 2017
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Machine learning models that remember too much
C. Song, T. Ristenpart, and V. Shmatikov · 2017
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Squeezedet: Unified, small, low power fully convolutional neural networks for real-time object detection for autonomous driving
B. Wu, F. N. Iandola, P. H. Jin, and K. Keutzer · 2017
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Wild patterns: Ten years after the rise of adversarial machine learning
B. Biggio and F. Roli · 2018
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Vggface2: A dataset for recognising faces across pose and age
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A self-driving robot using deep convolutional neural networks on neuromorphic hardware
T. Hwu, J. Isbell, N. Oros, and J. Krichmar · 2017
Cited alongside, same era.
Adversarial examples in the physical world
A. Kurakin, I. J. Goodfellow, and S. Bengio · 2017
Cited alongside, same era.
Adversarial frontier stitching for remote neural network watermarking
E. Le Merrer, P. Perez, and G. Trédan · 2017
Cited alongside, same era.
Magnet: A two-pronged defense against adversarial examples
D. Meng and H. Chen · 2017
Cited alongside, same era.
Practical black-box attacks against machine learning
N. Papernot, P. McDaniel, I. Goodfellow, S. Jha, Z. B. Celik, and A. Swami · 2017
Cited alongside, same era.
Deepxplore: Automated whitebox testing of deep learning systems
K. Pei, Y. Cao, J. Yang, and S. Jana · 2017
Cited alongside, same era.
https://github.com/tensorflow/cleverhans
Cleverhans code
Cited in the paper.
Q. Cao, L. Shen, W. Xie, O. M. Parkhi, and A. Zisserman · 2018
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Have you stolen my model? evasion attacks against deep neural network watermarking techniques
D. Hitaj and L. V. Mancini · 2018
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Trojaning attack on neural networks
Y. Liu, S. Ma, Y. Aafer, W.-C. Lee, J. Zhai, W. Wang, and X. Zhang · 2018
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Digital watermarking for deep neural networks
Y. Nagai, Y. Uchida, S. Sakazawa, and S. Satoh · 2018
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Feature squeezing: Detecting adversarial examples in deep neural networks
W. Xu, D. Evans, and Y. Qi · 2018
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