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Watermarking of deep neural networks (DNN) can enable their tracing once released by a data owner.
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Embedding Watermarks into Deep Neural Networks. In Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval (Bucharest, Romania) (ICMR ’17) . ACM, New York, NY, USA, 269–277
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Turning Your Weakness Into a Strength: Watermarking Deep Neural Networks by Backdooring. In Proceedings of the 27th USENIX Security Symposium (USENIX Security) . 1615–1631
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Property inference attacks on fully connected neural networks using permutation invariant representations. In Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security . ACM, 619–633
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Piracy Resistant Watermarks for Deep Neural Networks
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DeepSigns: An End-to-End Watermarking Framework for Ownership Protection of Deep Neural Networks. In Proceedings of the Twenty-Fourth International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) . 485–497
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On the Robustness of the Backdoor-based Watermarking in Deep Neural Networks
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DAWN: Dynamic Adversarial Watermarking of Neural Networks
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Large-scale celebfaces attributes (celeba) dataset
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BlackMarks: Blackbox Multibit Watermarking for Deep Neural Networks
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REFIT: a Unified Watermark Removal Framework for Deep Learning Systems with Limited Data
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Evasion Attacks Against Watermarking Techniques found in MLaaS Systems. In Proceedings of the 6th International Conference on Software Defined Systems (SDS) . 55–63
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PRADA: Protecting Against DNN Model Stealing Attacks. In Proceedings of the IEEE European Symposium on Security and Privacy (EuroS&P) . 512–527
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How to Prove Your Model Belongs to You: A Blind-Watermark based Framework to Protect Intellectual Property of DNN. In Proceedings of the 35th Annual Computer Security Applications Conference (ACSAC)
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Fine-pruning: Defending against backdooring attacks on deep neural networks. In International Symposium on Research in Attacks, Intrusions, and Defenses . Springer, 273–294
Kang Liu, Brendan Dolan-Gavitt, and Siddharth Garg. 2018a
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Attacks on Digital Watermarks for Deep Neural Networks. In ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . 2622–2626
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Effectiveness of Distillation Attack and Countermeasure on Neural Network Watermarking
Ziqi Yang, Hung Dang, and Ee-Chien Chang. 2019 · 2019
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Neural Network Laundering: Removing Black-Box Backdoor Watermarks from Deep Neural Networks
William Aiken, Hyoungshick Kim, and Simon Woo. 2020 · 2020
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Adversarial frontier stitching for remote neural network watermarking
Erwan Le Merrer, Patrick Perez, and Gilles Trédan. 2020 · 2020
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Removing Backdoor-Based Watermarks in Neural Networks with Limited Data
Xuankai Liu, Fengting Li, Bihan Wen, and Qi Li. 2020 · 2020
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