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Machine learning models are typically made available to potential client users via inference APIs.
On the robustness of the backdoor-based watermarking in deep neural networks, 2019
Masoumeh Shafieinejad, Jiaqi Wang, Nils Lukas, Xinda Li, and Florian Kerschbaum · 1906
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Statistical Power Analysis for the Behavioral Sciences
Jacob Cohen · 1988
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli · 2003
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Labeled faces in the wild: A database for studying face recognition in unconstrained environments
Gary B. Huang, Manu Ramesh, Tamara Berg, and Erik Learned-Miller · 2007
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Image quality metrics: Psnr vs. ssim
A. Horé and D. Ziou · 2010
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Generative adversarial nets
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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Stealing machine learning models via prediction apis
Florian Tramèr, Fan Zhang, Ari Juels, Michael K Reiter, and Thomas Ristenpart · 2016
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Ntire 2017 challenge on single image super-resolution: Dataset and study
Eirikur Agustsson and Radu Timofte · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros · 2017
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Deep laplacian pyramid networks for fast and accurate super-resolution
Wei-Sheng Lai, Jia-Bin Huang, Narendra Ahuja, and Ming-Hsuan Yang · 2017
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Photo-realistic single image super-resolution using a generative adversarial network
C. Ledig, L. Theis, F. Huszár, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi · 2017
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Towards deep learning models resistant to adversarial attacks
Aleksander Madry, Aleksandar Makelov, Ludwig Schmidt, Dimitris Tsipras, and Adrian Vladu · 2017
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Practical black-box attacks against machine learning
Nicolas Papernot, Patrick McDaniel, Ian Goodfellow, Somesh Jha, Z Berkay Celik, and Ananthram Swami · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Jun-Yan Zhu, Taesung Park, Phillip Isola, and Alexei A Efros · 2017
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Turning your weakness into a strength: Watermarking deep neural networks by backdooring
Yossi Adi, Carsten Baum, Moustapha Cisse, Benny Pinkas, and Joseph Keshet · 2018
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Stargan: Unified generative adversarial networks for multi-domain image-to-image translation
Yunjey Choi, Minje Choi, Munyoung Kim, Jung-Woo Ha, Sunghun Kim, and Jaegul Choo · 2018
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Copycat cnn: Stealing knowledge by persuading confession with random non-labeled data
Jacson Rodrigues Correia-Silva, Rodrigo F Berriel, Claudine Badue, Alberto F de Souza, and Thiago Oliveira-Santos · 2018
Earlier work this paper cites.
Reverse engineering convolutional neural networks through side-channel information leaks
Weizhe Hua, Zhiru Zhang, and G. Edward Suh · 2018
Cited alongside, same era.
Model extraction warning in MLaaS paradigm
Manish Kesarwani, Bhaskar Mukhoty, Vijay Arya, and Sameep Mehta · 2018
Cited alongside, same era.
Defending against model stealing attacks using deceptive perturbations
Taesung Lee, Benjamin Edwards, Ian Molloy, and Dong Su · 2018
Cited alongside, same era.
Are gans created equal? a large-scale study
Mario Lucic, Karol Kurach, Marcin Michalski, Olivier Bousquet, and Sylvain Gelly · 2018
Cited alongside, same era.
Towards reverse-engineering black-box neural networks
Seong Joon Oh, Max Augustin, Mario Fritz, and Bernt Schiele · 2018
Cited alongside, same era.
Forgotten siblings: Unifying attacks on machine learning and digital watermarking
Thieves of sesame street: Model extraction on bert-based apis
Kalpesh Krishna, Gaurav Singh Tomar, Ankur Parikh, Nicolas Papernot, and Mohit Iyyer · 2020
Later among the works it cites.
Prediction poisoning: Towards defenses against dnn model stealing attacks
Tribhuvanesh Orekondy, Bernt Schiele, and Mario Fritz · 2020
Later among the works it cites.
Dawn: Dynamic adversarial watermarking of neural networks
Sebastian Szyller, Buse Gul Atli, Samuel Marchal, and N. Asokan · 2020
Later among the works it cites.
Model extraction attacks against recurrent neural networks
Tatsuya Takemura, Naoto Yanai, and Toru Fujiwara · 2020
Later among the works it cites.
Deepfakes and beyond: A survey of face manipulation and fake detection
Ruben Tolosana, Ruben Vera-Rodriguez, Julian Fierrez, Aythami Morales, and Javier Ortega-Garcia · 2020
Later among the works it cites.
Cache telepathy: Leveraging shared resource attacks to learn DNN architectures
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E. Quiring, D. Arp, and K. Rieck · 2018
Cited alongside, same era.
Protecting intellectual property of deep neural networks with watermarking
Jialong Zhang, Zhongshu Gu, Jiyong Jang, Hui Wu, Marc Ph Stoecklin, Heqing Huang, and Ian Molloy · 2018
Cited alongside, same era.
CSI NN: Reverse engineering of neural network architectures through electromagnetic side channel
Lejla Batina, Shivam Bhasin, Dirmanto Jap, and Stjepan Picek · 2019
Cited alongside, same era.
Stealing neural networks via timing side channels
Vasisht Duddu, Debasis Samanta, D Vijay Rao, and Valentina E. Balas · 2019
Cited alongside, same era.
PRADA: protecting against DNN model stealing attacks
Mika Juuti, Sebastian Szyller, Samuel Marchal, and N. Asokan · 2019
Cited alongside, same era.
Defending against model stealing attacks with adaptive misinformation
Sanjay Kariyappa and Moinuddin K Qureshi · 2019
Cited alongside, same era.
A style-based generator architecture for generative adversarial networks
T. Karras, S. Laine, and T. Aila · 2019
Cited alongside, same era.
Mengjia Yan, Christopher W. Fletcher, and Josep Torrellas · 2020
Later among the works it cites.
Model watermarking for image processing networks
Jie Zhang, Dongdong Chen, Jing Liao, Han Fang, Weiming Zhang, Wenbo Zhou, Hao Cui, and Nenghai Yu · 2020
Later among the works it cites.
https://kaggle.com/balraj98/monet2photo
Cyclegan’s monet paintings and natural photos dataset · 2021
Closest in time.
https://kaggle.com/puneet6060/intel-image-classification
Intel image scene classification · 2021
Closest in time.
https://kaggle.com/arnaud58/landscape-pictures
Datasets of pictures of natural landscapes · 2021
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https://kaggle.com/arnaud58/selfie2anime
Picture datasets of selfie2anime · 2021
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Model extraction and defenses on generative adversarial networks, 2021
Hailong Hu and Jun Pang · 2021
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Entangled watermarks as a defense against model extraction
Hengrui Jia, Christopher A. Choquette-Choo, Varun Chandrasekaran, and Nicolas Papernot · 2021
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Sok: How robust is image classification deep neural network watermarking? (extended version)
Nils Lukas, Edward Jiang, Xinda Li, and Florian Kerschbaum · 2021
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Data poisoning won’t save you from facial recognition
Evani Radiya-Dixit and Florian Tramèr · 2021
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Selfie2anime
Nathan Glover Rico Beti · 2021
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Imitation attacks and defenses for black-box machine translation systems
Eric Wallace, Mitchell Stern, and Dawn Song · 2021
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Artificial fingerprinting for generative models: Rooting deepfake attribution in training data
Ning Yu, Vladislav Skripniuk, Sahar Abdelnabi, and Mario Fritz · 2021
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