Deep Neural Network (DNN) watermarking techniques are increasingly being used to protect the intellectual property of DNN models. Basically, DNN watermarking is a technique to insert side information into the DNN model without significantly degrading...
Deep neural network (DNN) watermarking is a potential approach for protecting the intellectual property rights of DNN models. Similar to classical watermarking techniques for multimedia content, the requirements for DNN watermarking include capacity,...
Due to their considerable costs, deep neural networks (DNNs) are valuable assets that need to be protected in terms of intellectual property (IP). From this statement, DNN watermarking gains significant interest since it allows DNN owners to prove th...
Federated learning (FL) is a technique that allows multiple participants to collaboratively train a Deep Neural Network (DNN) without the need to centralize their data. Among other advantages, it comes with privacy-preserving properties, making it at...
Traditional image watermarking technology focuses on the robustness and imperceptibility of the copyright information embedded in the cover image. However, in addition to copyright theft, the cover images stored and transmitted in the open network en...
Benefiting from the rapid development of computer hardware and big data, deep neural networks (DNNs) have been widely applied in commercial speaker recognition systems, achieving a kind of symmetry between “machine-learning-as-a-service”...
As training Deep Neural Networks (DNNs) becomes more expensive, the interest in protecting the ownership of the models with watermarking techniques increases. Uchida et al. proposed a digital watermarking algorithm that embeds the secret message into...
The metaverse-related content market is active and the demand for immersive content is increasing. However, there is no definition for granting copyrights to the content produced using artificial intelligence and discussions are still ongoing. We exp...
Existing model watermarking methods fail to provide adequate protection for edge intelligence models. This paper innovatively integrates the characteristics of model fingerprinting, proposing a model watermarking method named FingerMarks that enables...
This paper proposes a method to embed and extract a watermark on a digital hologram using a deep neural network. The entire algorithm for watermarking digital holograms consists of three sub-networks. For the robustness of watermarking, an attack sim...
Deep neural network (DNN) watermarking is a suitable method for protecting the ownership of deep learning (DL) models. It secretly embeds an identifier within the model, which can be retrieved by the owner to prove ownership. In this paper, we first...
Image steganography is a subfield of pattern recognition. It involves hiding secret data in a cover image and extracting the secret data from the stego image (described as a container image) when needed. Existing image steganography methods based on...
In the past years, Deep Neural Networks (DNNs) have become popular in many disciplines such as Computer Vision (CV), and the evolution of hardware has helped researchers to develop many powerful Deep Learning (DL) models to deal with several problems...
Recent studies on watermarking techniques based on image carriers have demonstrated new approaches that combine adversarial perturbations against steganalysis with embedding distortions. However, while these methods successfully counter convolutional...