Add to ORKGIn this work, we propose a set-membership inference attack for generative models using deep image watermarking techniques. In particular, we demonstrate how conditional sampling from a generative model can reveal the watermark that was injected into parts of the training data. Our empirical results demonstrate that the proposed watermarking technique is a principled approach for detecting the non-consensual use of image data in training generative models.Comment: Preliminary wor
Machine learning (ML) has become a core component of many real-world applications and training data ...
In recent years, various watermarking methods were suggested to detect computer vision models obtain...
International audienceRecently, it has been shown that Machine Learning models can leak sensitive in...
In this work, we propose a set-membership inference attack for generative models using deep image wa...
We present two information leakage attacks that outperform previous work on membership inference aga...
Deep learning has achieved overwhelming success, spanning from discriminative models to generative m...
Watermarking generative models consists of planting a statistical signal (watermark) in a model's ou...
Watermarking generative models consists of planting a statistical signal (watermark) in a model’s ou...
Abstract Machine learning has become an integral part of modern intelligent systems in all aspects o...
How much does a machine learning algorithm leak about its training data, and why? Membership inferen...
Photorealistic image generation has reached a new level of quality due to the breakthroughs of gener...
While machine learning (ML) has made tremendous progress during the past decade, recent research has...
Machine learning models are often trained on sensitive and proprietary datasets. Yet what -- and und...
Intellectual property protection of deep neural networks is receiving attention from more and more r...
Datasets are gaining more importance and economic value, since they are usedfor verification of publ...
Machine learning (ML) has become a core component of many real-world applications and training data ...
In recent years, various watermarking methods were suggested to detect computer vision models obtain...
International audienceRecently, it has been shown that Machine Learning models can leak sensitive in...
In this work, we propose a set-membership inference attack for generative models using deep image wa...
We present two information leakage attacks that outperform previous work on membership inference aga...
Deep learning has achieved overwhelming success, spanning from discriminative models to generative m...
Watermarking generative models consists of planting a statistical signal (watermark) in a model's ou...
Watermarking generative models consists of planting a statistical signal (watermark) in a model’s ou...
Abstract Machine learning has become an integral part of modern intelligent systems in all aspects o...
How much does a machine learning algorithm leak about its training data, and why? Membership inferen...
Photorealistic image generation has reached a new level of quality due to the breakthroughs of gener...
While machine learning (ML) has made tremendous progress during the past decade, recent research has...
Machine learning models are often trained on sensitive and proprietary datasets. Yet what -- and und...
Intellectual property protection of deep neural networks is receiving attention from more and more r...
Datasets are gaining more importance and economic value, since they are usedfor verification of publ...
Machine learning (ML) has become a core component of many real-world applications and training data ...
In recent years, various watermarking methods were suggested to detect computer vision models obtain...
International audienceRecently, it has been shown that Machine Learning models can leak sensitive in...