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Digital watermarking for deep neural networks

Yuki Nagai, Yusuke Uchida, Shigeyuki Sakazawa, Shin'ichi Satoh
2018 International Journal of Multimedia Information Retrieval  
In this paper, we propose a digital watermarking technology for ownership authorization of deep neural networks. First, we formulate a new problem: embedding watermarks into deep neural networks.  ...  We also define requirements, embedding situations, and attack types on watermarking in deep neural networks.  ...  In the proposed digital watermarking approach for deep neural network models, we make an assumption that the weight values are visible.  ... 
doi:10.1007/s13735-018-0147-1 fatcat:agb6aopi4zfxtgusj5j6wryyey

A General Approach for Using Deep Neural Network for Digital Watermarking [article]

Yurui Ming, Weiping Ding, Zehong Cao, Chin-Teng Lin
2020 arXiv   pre-print
In this paper, we propose a general deep neural network (DNN) based watermarking method to fulfill this goal.  ...  Instead of training a neural network for protecting a specific image, we train on an image set and use the trained model to protect a distinct test image set in a bulk manner.  ...  Hence, neural network especially the deep neural network (DNN) that exhibits high linearity, can be a candidate approach.  ... 
arXiv:2003.12428v1 fatcat:a6njlwicsbgkdi7cuwf2eq6so4

A Generalized Deep Neural Network Approach for Digital Watermarking Analysis

Weiping Ding, Yurui Ming, Zehong Cao, Chin-Teng Lin
2021 IEEE Transactions on Emerging Topics in Computational Intelligence  
In this paper, we propose a deep neural network (DNN) based watermarking method to achieve this goal.  ...  Instead of training a neural network for protecting a specific image, we train the network on an image dataset and generalize the trained model to protect distinct test images in a bulk manner.  ...  DING et al.: GENERALIZED DEEP NEURAL NETWORK APPROACH FOR DIGITAL WATERMARKING ANALYSIS Authorized licensed use limited to: Nan Tong University.  ... 
doi:10.1109/tetci.2021.3055520 fatcat:d4ys26fphrendiqvuayykotuoq

A Computational Modelling and Algorithmic Design Approach of Digital Watermarking in Deep Neural Networks

Revanna Sidamma Kavitha, Uppara Eranna, Mahendra Nanjappa Giriprasad
2020 Advances in Science, Technology and Engineering Systems  
In this paper we propose an algorithmic approach for Convolutional Neural Network (CNN) for digital watermarking which outperforms the existing frequency domain techniques in all aspects including security  ...  This research addresses digital watermarking in deep neural networks and with comprehensive experiments through computational modeling and algorithm design, we examine the performance of the built system  ...  process of digital watermarking using deep neural network and the Algorithm 2 presents the decoding process of digital watermarking using deep neural network.  ... 
doi:10.25046/aj0506187 fatcat:7mv5wcjrwjdabojrjfkcpf4qqa

An Image Compression Based Technique to Watermark a Neural Network

We propose in this paper a digital watermarking system for neural networks.  ...  Finally, we perform detailed image data experiments to demonstrate the potential of neural networks watermarking as the basis for this research attempt.  ...  We emphasis on how the copyrights of trained models can be protected computationally and propose for neural networks a digital watermarking technology [4] .  ... 
doi:10.35940/ijitee.d9064.029420 fatcat:hwvatnwyojgwrgj2bn52ejmwjm

Advanced Machine Learning Models to Handle Unifying Attacks in Images

Digital Watermarking is one of the approach to handle adversary related security approach to handle attacks appeared in digital environment.  ...  It uses Integrated CAPTCHA procedure to provide machine learning based captcha generation for user login and registration to handle different types of attacks in digital systems.  ...  Index Terms: Machine learning, embedding watermarking, neural networks, digital watermarking. I.  ... 
doi:10.35940/ijitee.j9830.0881019 fatcat:ofrpveib4jff7ngbd26j6pnoiy

Digital Hologram Watermarking Based on Multiple Deep Neural Networks Training Reconstruction and Attack

Ji-Won Kang, Jae-Eun Lee, Jang-Hwan Choi, Woosuk Kim, Jin-Kyum Kim, Dong-Wook Kim, Young-Ho Seo
2021 Sensors  
The entire algorithm for watermarking digital holograms consists of three sub-networks. For the robustness of watermarking, an attack simulation is inserted inside the deep neural network.  ...  This paper proposes a method to embed and extract a watermark on a digital hologram using a deep neural network.  ...  Figure 5 . 5 Training methodology of the deep neural network for watermarking.  ... 
doi:10.3390/s21154977 fatcat:mr5jautennajjh3npfiq5cjcxq

A novel method for identifying the deep neural network model with the Serial Number [article]

XiangRui Xu, YaQin Li, Cao Yuan
2019 arXiv   pre-print
In this paper, we put forth a new framework of the trigger-set watermark by embedding a unique Serial Number (relatedness less original labels) to the deep neural network for model ownership identification  ...  Deep neural network (DNN) with the state of art performance has emerged as a viable and lucrative business service.  ...  CONCLUSION In this paper, we propose a novel method to identify the deep neural network models for intellectual property protection.  ... 
arXiv:1911.08053v1 fatcat:othkd6t63jfzjgzogjxntbqiau

Embedding Watermarks into Deep Neural Networks

Yusuke Uchida, Yuki Nagai, Shigeyuki Sakazawa, Shin'ichi Satoh
2017 Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval - ICMR '17  
Firstly, we formulate a new problem: embedding watermarks into deep neural networks. We also define requirements, embedding situations, and attack types for watermarking to deep neural networks.  ...  Sharing trained models of these deep neural networks is very important in the rapid progress of researching or developing deep neural network systems.  ...  We formulate a new problem: embedding watermarks in deep neural networks. We also define requirements, embedding situations, and attack types for watermarking deep neural networks. 2.  ... 
doi:10.1145/3078971.3078974 dblp:conf/mir/UchidaNSS17 fatcat:mstmlza5ljbmfonm7kj5746hb4

Exploring Artificial Neural Networks in Cryptography – A Deep Insight

Manikandan N
2020 International Journal of Emerging Trends in Engineering Research  
Also, application of Neural networks for cryptography related problems yielded positive results in almost all the applied fields.  ...  Despite the considerable number of strategies, applications of Artificial neural networks (ANN) for cryptographic problems appeared to be more remarkable.  ...  NEURAL NETWORKS FOR DIGITAL WATERMARKING Watermarking is another old technique that existed back in the thirteenth century. Initially, watermarking was used in the papermaking industry.  ... 
doi:10.30534/ijeter/2020/146872020 fatcat:wqtgwcxwgbbt3pr2tpinq2goiu

Robust Black-box Watermarking for Deep NeuralNetwork using Inverse Document Frequency [article]

Mohammad Mehdi Yadollahi, Farzaneh Shoeleh, Sajjad Dadkhah, Ali A. Ghorbani
2021 arXiv   pre-print
Recently, these Machine Learning (ML) methods, such as Deep Neural Networks (DNNs), presented exceptional achievement in implementing human-level capabilities for various predicaments, such as Natural  ...  To this end, we propose a framework for watermarking a DNN model designed for a textual domain.  ...  The combination of deep learning and neural networks are called deep neural networks (DNNs).  ... 
arXiv:2103.05590v1 fatcat:esfm4plqjjgwjobal2nuwuh7be

Digital Passport: A Novel Technological Strategy for Intellectual Property Protection of Convolutional Neural Networks [article]

Lixin Fan and KamWoh Ng and Chee Seng Chan
2019 arXiv   pre-print
In order to prevent deep neural networks from being infringed by unauthorized parties, we propose a generic solution which embeds a designated digital passport into a network, and subsequently, either  ...  Extensive experiments also show that the deep neural network performance under unauthorized usages deteriorate significantly (e.g. with 33% to 82% reductions of CIFAR10 classification accuracies), while  ...  Discussions and Conclusions We renovated the paradigm in recent studies of digital watermarking for deep neural network protections, by proposing to paralyze network functionalities for unauthorized usages  ... 
arXiv:1905.04368v1 fatcat:fp24tjqsg5btthbjdtnwgpydva

' Identity bracelets ' for deep neural networks

Xiangrui Xu, Yaqin Li, Cao Yuan
2020 IEEE Access  
Therefore, we propose an embedded 'identity bracelet' for deep neural networks that acts as proof of a model's owner.  ...  Our solution is an extension to the existing trigger-set watermarking techniques that embeds a post-cryptographic-style serial number into the base deep neural network (DNN).  ...  neural network for DNN-SN embedding.  ... 
doi:10.1109/access.2020.2998784 fatcat:bwp3fuxy2bdsvpmxepucwalirq

DeepSigns: A Generic Watermarking Framework for IP Protection of Deep Learning Models [article]

Bita Darvish Rouhani and Huili Chen and Farinaz Koushanfar
2018 arXiv   pre-print
Proof-of-concept evaluations on MNIST, and CIFAR10 datasets, as well as a wide variety of neural network architectures including Wide Residual Networks, Convolution Neural Networks, and Multi-Layer Perceptrons  ...  This paper proposes DeepSigns, a novel end-to-end IP protection framework that enables insertion of coherent digital watermarks in contemporary DL models.  ...  Embedding digital watermarks into deep neural networks is a key enabler for reliable technology transfer.  ... 
arXiv:1804.00750v2 fatcat:2n4gb6gt2zenlbhoaaa2tvtesq

Framework for Improvising Dual Digital Watermarking through Deep Learning Techniques

Saranya. G, Mrs. Priya Vijay
2018 International Journal of Engineering Research and  
Achieving better compression rates in dual digital watermarking is still area of concern. Digital watermarking has four techniques for compression the image.  ...  for privacy data.  ...  III FRAMEWORK MODEL The proposed system implements Convolutional Neural Network(CNN) is the deep class that is it is implemented by Forward Neural Networks(FNN) which is used to analysis the visual image  ... 
doi:10.17577/ijertv7is020138 fatcat:bfqj7rm3k5hlje5ibtqhnlw6di
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