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A Survey of Image Information Hiding Algorithms Based on Deep Learning

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Computer Modeling in Engineering & Sciences 2018年第12期117卷 425-454页

作者： Ruohan Meng Qi Cui chengsheng yuan School of Computer and Software Nanjing University of Information Science and TechnologyNing Liu RoadNo.219Nanjing210044China Jiangsu Engineering Centre of Network Monitoring Ning Liu RoadNo.219Nanjing210044China Department of Electrical and computer Engineering University of Windsor401 Sunset AvenueWindsorONN9B 374Canada.

With the development of data science and technology,information security has been further *** order to solve privacy problems such as personal privacy being peeped and copyright being infringed,information hiding algorithms has been *** information hiding is to make use of the redundancy of the cover image to hide secret information in *** that the stego image cannot be distinguished from the cover image,and sending secret information to receiver through the transmission of the stego *** present,the model based on deep learning is also widely applied to the field of information *** paper makes an overall conclusion on image information hiding based on deep *** is divided into four parts of steganography algorithms,watermarking embedding algorithms,coverless information hiding algorithms and steganalysis algorithms based on deep *** these four aspects,the state-of-the-art information hiding technologies based on deep learning are illustrated and analyzed.

关键词： Steganography deep learning steganalysis watermarking coverless information hiding.

A Novel Steganography Algorithm Based on Instance Segmentation

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Computers, Materials & Continua 2020年第4期63卷 183-196页

作者： Ruohan Meng Qi Cui Zhili Zhou chengsheng yuan Xingming Sun School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Jiangsu Engineering Centre of Network Monitoring Nanjing210044China Department of Electrical and Computer Engineering University of WindsorWindsorCanada

Information hiding tends to hide secret information in image area where is rich texture or high frequency,so as to transmit secret information to the recipient without affecting the visual quality of the image and arousing *** take advantage of the complexity of the object texture and consider that under certain circumstances,the object texture is more complex than the background of the image,so the foreground object is more suitable for steganography than the *** the basis of instance segmentation,such as Mask R-CNN,the proposed method hides secret information into each object's region by using the masks of instance segmentation,thus realizing the information hiding of the foreground object without *** method not only makes it more efficient for the receiver to extract information,but also proves to be more secure and robust by experiments.

关键词： Steganography object detection mask R-CNN irregular region

Local Adaptive Gradient Variance Attack for Deep Fake Fingerprint Detection

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Computers, Materials & Continua 2024年第1期78卷 899-914页

作者： chengsheng yuan Baojie Cui Zhili Zhou Xinting Li Qingming Jonathan Wu Engineering Research Center of Digital Forensics Ministry of EducationNanjing University of Information Science and TechnologyNanjing210044China School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China Institute of Artificial Intelligence and Blockchain Guangzhou UniversityGuangzhou510006China School of International Relations National University of Defense TechnologyNanjing210039China Department of Electrical and Computer Engineering University of WindsorWindsorN9B 3P4Canada

In recent years,deep learning has been the mainstream technology for fingerprint liveness detection(FLD)tasks because of its remarkable ***,recent studies have shown that these deep fake fingerprint detection(DFFD)models are not resistant to attacks by adversarial examples,which are generated by the introduction of subtle perturbations in the fingerprint image,allowing the model to make fake *** of the existing adversarial example generation methods are based on gradient optimization,which is easy to fall into local optimal,resulting in poor transferability of adversarial *** addition,the perturbation added to the blank area of the fingerprint image is easily perceived by the human eye,leading to poor visual *** response to the above challenges,this paper proposes a novel adversarial attack method based on local adaptive gradient variance for *** ridge texture area within the fingerprint image has been identified and designated as the region for perturbation ***,the images are fed into the targeted white-box model,and the gradient direction is optimized to compute gradient ***,an adaptive parameter search method is proposed using stochastic gradient ascent to explore the parameter values during adversarial example generation,aiming to maximize adversarial attack *** results on two publicly available fingerprint datasets show that ourmethod achieves higher attack transferability and robustness than existing methods,and the perturbation is harder to perceive.

关键词： FLD adversarial attacks adversarial examples gradient optimization transferability

A Lightweight Convolutional Neural Network with Representation Self-challenge for Fingerprint Liveness Detection

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Computers, Materials & Continua 2022年第10期73卷 719-733页

作者： Jie Chen chengsheng yuan Chen Cui Zhihua Xia Xingming Sun Thangarajah Akilan School of Computer Science Nanjing University of Information Science and TechnologyNanjing210044China Key Laboratory of Public Security Information Application Based on Big-Data Architecture Ministry of Public SecurityZhejiang Police CollegeHangzhou310053China Jiangsu Yuchi Blockchain Research Institute Nanjing210044China Department of Software Engineering Lakehead UniversityThunder BayON P7B 5E1Canada

Fingerprint identification systems have been widely deployed in many occasions of our daily ***,together with many advantages,they are still vulnerable to the presentation attack(PA)by some counterfeit *** address challenges from PA,fingerprint liveness detection(FLD)technology has been proposed and gradually attracted people’s *** vast majority of the FLD methods directly employ convolutional neural network(CNN),and rarely pay attention to the problem of overparameterization and over-fitting of models,resulting in large calculation force of model deployment and poor model *** at filling this gap,this paper designs a lightweight multi-scale convolutional neural network method,and further proposes a novel hybrid spatial pyramid pooling block to extract abundant features,so that the number of model parameters is greatly reduced,and support multi-scale true/fake fingerprint ***,the representation self-challenge(RSC)method is used to train the model,and the attention mechanism is also adopted for optimization during execution,which alleviates the problem of model over-fitting and enhances generalization of detection ***,experimental results on two publicly benchmarks:LivDet2011 and LivDet2013 sets,show that our method achieves outstanding detection results for blind materials and *** size of the model parameters is only 548 KB,and the average detection error of cross-sensors and cross-materials are 15.22 and 1 respectively,reaching the highest level currently available.

关键词： FLD lightweight multi-scale RSC blind materials

A Rasterized Lightning Disaster Risk Method for Imbalanced Sets Using Neural

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Computers, Materials & Continua 2021年第1期66卷 563-574页

作者： Yan Zhang Jin Han chengsheng yuan Shuo Yang Chuanlong Li Xingming Sun Nanjing University of Information Science&Technology Nanjing210044China Engineering Research Center of Digital Forensics Ministry of EducationNanjing201144China Waterford Institute of Technology WaterfordX91K0EKIreland

Over the past 10 years,lightning disaster has caused a large number of casualties and considerable economic loss *** poses a huge threat to various *** an attempt to reduce the risk of lightning-caused disaster,many scholars have carried out in-depth research on ***,these studies focus primarily on the lightning itself and other meteorological elements are *** addition,the methods for assessing the risk of lightning disaster fail to give detailed attention to regional features(lightning disaster risk).This paper proposes a grid-based risk assessment method based on data from multiple ***,this paper considers the impact of lightning,the population density,the economy,and geographical environment data on the occurrence of lightning disasters;Second,this paper solves the problem of imbalanced lightning disaster data in geographic grid samples based on the K-means clustering algorithm;Third,the method calculates the feature of lightning disaster in each small field with the help of neural network structure,and the calculation results are then visually reflected in a zoning map by the Jenks natural breaks *** experimental results show that our method can solve the problem of imbalanced lightning disaster data,and offer 81%accuracy in lightning disaster risk assessment.

关键词： Lightning disaster neural network imbalanced data

Fingerprint Liveness Detection from Different Fingerprint Materials Using Convolutional Neural Network and Principal Component Analysis

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Computers, Materials & Continua 2017年第4期53卷 357-372页

作者： chengsheng yuan Xinting Li Q.M.Jonathan Wu Jin Li Xingming Sun School of Computer and Software Nanjing University of Information Science&TechnologyNing Liu RoadNo.219NanjingChina210044 Jiangsu Engineering Center of Network Monitoring Ning Liu RoadNo.219NanjingChina210044 Department of Electrical and Computer Engineering University of Windsor401 Sunset AvenueWindsorONCanada N9B 3P4 School of Computer Science Guangzhou UniversityYudongxi Road 36Tianhe DistrictGuangzhouChina510500

Fingerprint-spoofing attack often occurs when imposters gain access illegally by using artificial fingerprints,which are made of common fingerprint materials,such as silicon,latex,***,to protect our privacy,many fingerprint liveness detection methods are put forward to discriminate fake or true *** work on liveness detection for fingerprint images is focused on the construction of complex handcrafted features,but these methods normally destroy or lose spatial information between *** from existing methods,convolutional neural network(CNN)can generate high-level semantic representations by learning and concatenating low-level edge and shape features from a large amount of labeled ***,CNN is explored to solve the above problem and discriminate true fingerprints from fake ones in this *** reduce the redundant information and extract the most distinct features,ROI and PCA operations are performed for learned features of convolutional layer or pooling *** that,the extracted features are fed into SVM *** results based on the LivDet(2013)and the LivDet(2011)datasets,which are captured by using different fingerprint materials,indicate that the classification performance of our proposed method is both efficient and convenient compared with the other previous methods.

关键词： Fingerprint liveness detection CNNs PCA SVM ROI LivDet 2013 LivDet 2011

OPPR:An Outsourcing Privacy-Preserving JPEG Image Retrieval Scheme with Local Histograms in Cloud Environment

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Journal on Big Data 2021年第1期3卷 21-33页

作者： Jian Tang Zhihua Xia Lan Wang chengsheng yuan Xueli Zhao Nanjing University of Information Science&Technology Nanjing210044China

As the wide application of imaging technology,the number of big image data which may containing private information is growing *** to insufficient computing power and storage space for local server device,many people hand over these images to cloud servers for *** actually,it is unsafe to store the images to the cloud,so encryption becomes a necessary step before uploading to reduce the risk of privacy ***,it is not conducive to the efficient application of image,especially in the Content-Based Image Retrieval(CBIR)*** paper proposes an outsourcing privacy-preserving JPEG CBIR *** design a set of JPEG format-compatible encryption method,making no file expansion to JPEG *** firstly combine multiple adjacent 8×8 DCT coefficient blocks into ***,random scrambling and stream encryption are used on the binary code of DCT coefficients to protect the JPEG image *** task of extracting features from encrypted images and retrieving similar images are done by the cloud *** group index histograms of DCT coefficients are extracted from the encrypted big-blocks,then the global vector is produced to represent the JPEG image with the aid of bag-of-words(BOW)*** security analysis and experimental results show that our proposed scheme has strong security and good retrieval performance.

关键词： JPEG image retrieval DCT coefficients BOW format-compatible

基于差分隐私的深度伪造指纹检测模型版权保护算法

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通信学报 2022年第9期43卷 181-193页

作者：袁程胜郭强付章杰南京信息工程大学计算机学院、软件学院、网络空间安全学院江苏南京210044 南京信息工程大学数字取证教育部工程研究中心江苏南京210044

提出了一种基于差分隐私的深度伪造指纹检测模型版权保护算法,在不削弱原始任务性能的同时,实现了深度伪造指纹检测模型版权的主动保护和被动验证。在原始任务训练时,通过添加噪声以引入随机性,利用差分隐私算法的期望稳定性进行分类决... 详细信息

提出了一种基于差分隐私的深度伪造指纹检测模型版权保护算法,在不削弱原始任务性能的同时,实现了深度伪造指纹检测模型版权的主动保护和被动验证。在原始任务训练时,通过添加噪声以引入随机性,利用差分隐私算法的期望稳定性进行分类决策,以削弱对噪声的敏感。在被动验证中,利用FGSM生成对抗样本,通过微调决策边界以建立后门,将后门映射关系作为植入水印实现被动验证。为了解决多后门造成的版权混淆,设计了一种水印验证框架,对触发后门加盖时间戳,借助时间顺序来鉴别版权。在主动保护中,为了给用户提供分等级的服务,通过概率选择策略冻结任务中的关键性神经元,设计访问权限实现神经元的解冻,以获得原始任务的使用权。实验结果表明,不同模型性能下的后门验证依然有效,嵌入的后门对模型修改表现出稳健性。此外,所提算法不但能抵挡攻击者策反合法用户实施的合谋攻击,而且能抵挡模型修改发动的微调、压缩等攻击。

关键词：版权保护对抗样本差分隐私模型水印伪造指纹检测

A Novel Steganography Scheme Combining Coverless Information Hiding and Steganography

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Journal of Information Hiding and Privacy Protection 2019年第1期1卷 43-48页

作者： Ruohan Meng Zhili Zhou Qi Cui Xingming Sun chengsheng yuan School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Jiangsu Engineering Centre of Network Monitoring Nanjing210044China Department of Electrical and computer Engineering University of WindsorWindsorONCanada N9B 3P4

At present,the coverless information hiding has been ***,due to the limited mapping relationship between secret information and feature selection,it is challenging to further enhance the hiding capacity of coverless information *** the same time,the steganography algorithm based on object detection only hides secret information in foreground objects,which contribute to the steganography capacity is *** object recognition contains multiple objects and location,secret information can be mapped to object categories,the relationship of location and so ***,this paper proposes a new steganography algorithm based on object detection and relationship mapping,which integrates coverless information hiding and *** this method,the coverless information hiding is realized by mapping the object type,color and secret information in object detection *** the same time,the object detection method is used to find the safe area to hide secret *** proposed algorithm can not only improve the steganographic capacity of the two information hiding methods but also make the coverless information hiding more secure and robust.

关键词： Steganography faster R-CNN coverless information hiding