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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  ...  along with the criteria in the neural networks such as conditions embedded, and types of watermarking attack.  ...  Conclusions In this paper, we proposed a learning framework for robust digital image watermarking technique based on deep neural network.  ... 
doi:10.25046/aj0506187 fatcat:7mv5wcjrwjdabojrjfkcpf4qqa

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  
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 simulation is inserted inside the deep neural network.  ...  Figure 5 . 5 Training methodology of the deep neural network for watermarking.  ... 
doi:10.3390/s21154977 fatcat:mr5jautennajjh3npfiq5cjcxq

Digital watermarking for deep neural networks

Yuki Nagai, Yusuke Uchida, Shigeyuki Sakazawa, Shin'ichi Satoh
2018 International Journal of Multimedia Information Retrieval  
We also define requirements, embedding situations, and attack types on watermarking in deep neural networks.  ...  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.  ...  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 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.  ...  THE SECURITY OF DNN SN As we above mentioned tempering attacks, one can forge a counterfeit watermark for any label-based watermarking model.  ... 
arXiv:1911.08053v1 fatcat:othkd6t63jfzjgzogjxntbqiau

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  ...  Deep learning techniques are one of the most significant elements of any Artificial Intelligence (AI) services.  ...  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

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.  ...  The paper explains the state of art for all four techniques and reveals the importance of embedding of fragile and robust watermark during compression on the image encoder.  ...  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

Optimized DWT Based Digital Image Watermarking and Extraction Using RNN-LSTM

R. Radha Kumari, V. Vijaya Kumar, K. Rama Naidu
2021 International Journal of Interactive Multimedia and Artificial Intelligence  
After performing the embedding process, the extraction is processed by deep neural network concept of Recurrent Neural Network based Long Short-Term Memory (RNN-LSTM).  ...  Therefore, to enhance the robustness, optimization techniques and deep neural network concepts are utilized.  ...  on embedding strategy. • The watermark image extraction process is performed based on a novel deep neural network concept called Recurrent Neural Network based Long Short-Term Memory (RNN-LSTM). • The  ... 
doi:10.9781/ijimai.2021.10.006 fatcat:dwr6zwpevbfszmeefhajh6c23m

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

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

Watermarking Graph Neural Networks based on Backdoor Attacks [article]

Jing Xu, Stjepan Picek
2021 arXiv   pre-print
Graph Neural Networks (GNNs) have achieved promising performance in various real-world applications.  ...  We 1) design two strategies to generate watermarked data for the graph classification and one for the node classification task, 2) embed the watermark into the host model through training to obtain the  ...  All the methods mentioned above focus on the watermarking technique for deep neural networks.  ... 
arXiv:2110.11024v2 fatcat:hhds4cbjwrhwrauocjbb3vzgni

Have You Stolen My Model? Evasion Attacks Against Deep Neural Network Watermarking Techniques [article]

Dorjan Hitaj, Luigi V. Mancini
2018 arXiv   pre-print
This paper focuses on verifying the robustness and reliability of state-of- the-art deep neural network watermarking schemes.  ...  The increased cost of building a good deep neural network model gives rise to a need for protecting this investment from potential copyright infringements.  ...  ACKNOWLEDGMENTS The authors would like to thank Briland Hitaj for the valuable comments and discussions on this work.  ... 
arXiv:1809.00615v1 fatcat:6skk543x2jfftd3m66ofxdw7he

' 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).  ...  ANTI-COUNTERFEIT SYSTEM This section provides some relevant background on digital signature algorithms and their extensions as well as anti-counterfeiting serial number systems in deep neural networks.  ... 
doi:10.1109/access.2020.2998784 fatcat:bwp3fuxy2bdsvpmxepucwalirq

Digital Image Watermarking Processor Based on Deep Learning

Jae-Eun Lee, Ji-Won Kang, Woo-Suk Kim, Jin-Kyum Kim, Young-Ho Seo, Dong-Wook Kim
2021 Electronics  
Next, we analyze a fixed-point number system suitable for implementing neural networks as hardware for watermarking.  ...  Much research and development have been made to implement deep neural networks for various purposes with hardware. We implement the deep learning algorithm with a dedicated processor.  ...  Since we use a watermarking algorithm based on deep learning, we optimize the operation method of the neural network for deep learning according to the hardware implementation and operation.  ... 
doi:10.3390/electronics10101183 fatcat:obakkwjwjnclbcfk7i6qcz4kbu

A Compact Neural Network-based Algorithm for Robust Image Watermarking [article]

Hong-Bo Xu, Rong Wang, Jia Wei, Shao-Ping Lu
2021 arXiv   pre-print
In this paper, we propose a novel digital image watermarking solution with a compact neural network, named Invertible Watermarking Network (IWN).  ...  Our IWN architecture is based on a single Invertible Neural Network (INN), this bijective propagation framework enables us to effectively solve the challenge of message embedding and extraction simultaneously  ...  In recent years, deep neural networks have already been applied to digital image watermarking [7] , [8] , [12] - [17] .  ... 
arXiv:2112.13491v1 fatcat:4du3de57wjehxl2ldslir5xcy4
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