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The training and creation of deep learning model is usually costly, thus it can be regarded as an intellectual property (IP) of the model creator. However, malicious users who obtain high-performance models may illegally copy, redistribute,…

Cryptography and Security · Computer Science 2022-07-05 Mingfu Xue , Yushu Zhang , Jian Wang , Weiqiang Liu

Deep Neural Networks (DNNs), from AlexNet to ResNet to ChatGPT, have made revolutionary progress in recent years, and are widely used in various fields. The high performance of DNNs requires a huge amount of high-quality data, expensive…

Artificial Intelligence · Computer Science 2023-06-21 Yuchen Sun , Tianpeng Liu , Panhe Hu , Qing Liao , Shaojing Fu , Nenghai Yu , Deke Guo , Yongxiang Liu , Li Liu

The training of Deep Neural Networks (DNN) is costly, thus DNN can be considered as the intellectual properties (IP) of model owners. To date, most of the existing protection works focus on verifying the ownership after the DNN model is…

Cryptography and Security · Computer Science 2023-05-26 Mingfu Xue , Shichang Sun , Can He , Yushu Zhang , Jian Wang , Weiqiang Liu

Deep neural networks (DNNs) have achieved tremendous success in artificial intelligence (AI) fields. However, DNN models can be easily illegally copied, redistributed, or abused by criminals, seriously damaging the interests of model…

Cryptography and Security · Computer Science 2023-11-29 Xuefeng Fan , Dahao Fu , Hangyu Gui , Xinpeng Zhang , Xiaoyi Zhou

Deep learning techniques have made tremendous progress in a variety of challenging tasks, such as image recognition and machine translation, during the past decade. Training deep neural networks is computationally expensive and requires…

Cryptography and Security · Computer Science 2019-11-11 Zheng Li , Chengyu Hu , Yang Zhang , Shanqing Guo

Deep learning (DL) models, especially those large-scale and high-performance ones, can be very costly to train, demanding a great amount of data and computational resources. Unauthorized reproduction of DL models can lead to copyright…

Cryptography and Security · Computer Science 2021-12-13 Jialuo Chen , Jingyi Wang , Tinglan Peng , Youcheng Sun , Peng Cheng , Shouling Ji , Xingjun Ma , Bo Li , Dawn Song

Deep neural networks have had enormous impact on various domains of computer science, considerably outperforming previous state of the art machine learning techniques. To achieve this performance, neural networks need large quantities of…

Cryptography and Security · Computer Science 2018-09-05 Dorjan Hitaj , Luigi V. Mancini

Training high performance Deep Neural Networks (DNNs) models require large-scale and high-quality datasets. The expensive cost of collecting and annotating large-scale datasets make the valuable datasets can be considered as the…

Cryptography and Security · Computer Science 2023-05-26 Mingfu Xue , Yinghao Wu , Yushu Zhang , Jian Wang , Weiqiang Liu

Intellectual property (IP) protection for Deep Neural Networks (DNNs) has raised serious concerns in recent years. Most existing works embed watermarks in the DNN model for IP protection, which need to modify the model and lack of…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Mingfu Xue , Xin Wang , Yinghao Wu , Shifeng Ni , Yushu Zhang , Weiqiang Liu

Training a deep neural network (DNN) requires a high computational cost. Buying models from sellers with a large number of computing resources has become prevailing. However, the buyer-seller environment is not always trusted. To protect…

Cryptography and Security · Computer Science 2023-12-12 Yusheng Guo , Nan Zhong , Zhenxing Qian , Xinpeng Zhang

Deep Neural Networks (DNNs), as valuable intellectual property, face unauthorized use. Existing protections, such as digital watermarking, are largely passive; they provide only post-hoc ownership verification and cannot actively prevent…

Cryptography and Security · Computer Science 2025-12-12 Han Yang , Shaofeng Li , Tian Dong , Xiangyu Xu , Guangchi Liu , Zhen Ling

Deep Learning (DL) models have caused a paradigm shift in our ability to comprehend raw data in various important fields, ranging from intelligence warfare and healthcare to autonomous transportation and automated manufacturing. A practical…

Cryptography and Security · Computer Science 2018-06-04 Bita Darvish Rouhani , Huili Chen , Farinaz Koushanfar

Protecting the Intellectual Property Rights (IPR) associated to Deep Neural Networks (DNNs) is a pressing need pushed by the high costs required to train such networks and the importance that DNNs are gaining in our society. Following its…

Cryptography and Security · Computer Science 2021-03-18 Yue Li , Hongxia Wang , Mauro Barni

A well-trained DNN model can be regarded as an intellectual property (IP) of the model owner. To date, many DNN IP protection methods have been proposed, but most of them are watermarking based verification methods where model owners can…

Cryptography and Security · Computer Science 2023-05-26 Mingfu Xue , Zhiyu Wu , Jian Wang , Yushu Zhang , Weiqiang Liu

With the growing applications of Deep Learning (DL), especially recent spectacular achievements of Large Language Models (LLMs) such as ChatGPT and LLaMA, the commercial significance of these remarkable models has soared. However, acquiring…

Cryptography and Security · Computer Science 2024-11-11 Yongqi Jiang , Yansong Gao , Chunyi Zhou , Hongsheng Hu , Anmin Fu , Willy Susilo

Recently, the research on protecting the intellectual properties (IP) of deep neural networks (DNN) has attracted serious concerns. A number of DNN copyright protection methods have been proposed. However, most of the existing watermarking…

Artificial Intelligence · Computer Science 2022-07-05 Shichang Sun , Mingfu Xue , Jian Wang , Weiqiang Liu

With the broad application of deep neural networks, the necessity of protecting them as intellectual properties has become evident. Numerous watermarking schemes have been proposed to identify the owner of a deep neural network and verify…

Cryptography and Security · Computer Science 2021-08-23 Fang-Qi Li , Shi-Lin Wang , Alan Wee-Chung Liew

Illegitimate reproduction, distribution and derivation of Deep Neural Network (DNN) models can inflict economic loss, reputation damage and even privacy infringement. Passive DNN intellectual property (IP) protection methods such as…

Cryptography and Security · Computer Science 2025-06-02 Chaohui Xu , Qi Cui , Jinxin Dong , Weiyang He , Chip-Hong Chang

With substantial amount of time, resources and human (team) efforts invested to explore and develop successful deep neural networks (DNN), there emerges an urgent need to protect these inventions from being illegally copied, redistributed,…

Cryptography and Security · Computer Science 2019-11-05 Lixin Fan , Kam Woh Ng , Chee Seng Chan

The commercialization of deep learning creates a compelling need for intellectual property (IP) protection. Deep neural network (DNN) watermarking has been proposed as a promising tool to help model owners prove ownership and fight piracy.…

Machine Learning · Computer Science 2021-02-16 Jia Guo , Miodrag Potkonjak
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