检索结果-内蒙古大学图书馆

作者： Wu, Yulei Chen, Xianyi Sun, Xingming Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology China Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology China School of Computer and Software Nanjing University of Information Science and Technology China

Information hiding is an evolving and challenging research field. Lately, a novel information hiding method that utilizes the original cover without modification to transmit secret messages has raised attention of the scholars. This method, coverless information hiding, can resist various kinds of existing steganalysis techniques due to its property. In terms of text steganography, coverless information hiding methods have made headway, most of which aim at Chinese steganography. Thus, this paper proposes a coverless steganography based on English, using the tag based protocol to make the secret communication possible. Experimental results reveal that the proposed method has decent success rate and hiding capacity. © 2018 Taiwan Academic network Management Committee. All rights reserved.

关键词： Steganography

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Embedding Image Through Generated Intermediate Medium Using Deep Convolutional Generative Adversarial network

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computers, Materials & Continua 2018年第8期56卷 313-324页

作者： Chuanlong Li Yumeng Jiang Marta Cheslyar 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 School of Informatics University of EdinburghOld CollegeSouth BridgeEdinburghEH89YLUK

Deep neural network has proven to be very effective in computer vision *** convolutional network can learn the most suitable features of certain images without specific measure functions and outperform lots of traditional image processing *** adversarial network(GAN)is becoming one of the highlights among these deep neural *** is capable of generating realistic images which are imperceptible to the human vision system so that the generated images can be directly used as intermediate medium for many *** promising application of using GAN generated images would be image concealing which requires the embedded image looks like not being tampered to human vision system and also undetectable to most *** synthesizing has drawn lots of attention in computer vision field and is used for image concealing in steganography and *** traditional methods which use synthesized textures for information hiding mainly select features and mathematic functions by human metrics and usually have a low embedding *** paper takes advantage of the generative network and proposes an approach for synthesizing complex texture-like image of arbitrary size using a modified deep convolutional generative adversarial network(DCGAN),and then demonstrates the feasibility of embedding another image inside the generated texture while the difference between the two images is nearly invisible to the human eyes.

关键词： GAN,CNN,texture synthesis steganography watermark image concealing information hiding

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Full-Blind Delegating Private Quantum Computation

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computers, Materials & Continua 2018年第8期56卷 211-223页

作者： Wenjie Liu Zhenyu Chen Jinsuo Liu Zhaofeng Su Lianhua Chi Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science&TechnologyNanjing210044China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China State Grid Electric Power Research Institute NARI Group CorporationNanjing210003China Centre for Quantum Software and Information Faculty of Engineering and Information TechnologyUniversity of Technology SydneyNSW2007Australia Department of Computer Science and Information Technology La Trobe UniversityVIC3086Australia

The delegating private quantum computation(DQC)protocol with the universal quantum gate set{X,Z,H,P,R,CNOT}was firstly proposed by Broadbent et al.[Broadbent(2015)],and then Tan et al.[Tan and Zhou(2017)]tried to put forward a half-blind DQC protocol(HDQC)with another universal set{H,P,CNOT,T}.However,the decryption circuit of Toffoli gate(i.e.T)is a little redundant,and Tan et al.’s protocol[Tan and Zhou(2017)]exists the information *** addition,both of these two protocols just focus on the blindness of data(*** client’s input and output),but do not consider the blindness of computation(*** delegated quantum operation).For solving these problems,we propose a full-blind DQC protocol(FDQC)with quantum gate set{H,P,CNOT,T},where the desirable delegated quantum operation,one of{H,P,CNOT,T},is replaced by a fixed sequence(H,P,CZ,CNOT,T)to make the computation blind,and the decryption circuit of Toffoli gate is also *** shows that our protocol can not only correctly perform any delegated quantum computation,but also holds the characteristics of data blindness and computation blindness.

关键词： Delegating private quantum computation universal quantum gate set full-blind Toffoli gate circuit optimization

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Impact Damage Identification for Composite Material Based on Transmissibility Function and OS-ELM Algorithm

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Journal of Quantum Computing 2019年第1期1卷 1-8页

作者： Yajie Sun Yanqing Yuan Qi Wang Sai Ji Lihua Wang Shaoen Wu Jie Chen Qin Zhang Jiangsu engineering Centre of Network Monitoring Nanjing University of Information Science and TechnologyNanjing210044China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China School of Information and Control Nanjing University of Information Science and TechnologyNanjing210044China Department of Computer Science Ball State UniversityMuncieUSA

A method is proposed based on the transmissibility function and the OnlineSequence Extreme Learning Machine (OS-ELM) algorithm, which is applied to theimpact damage of composite materials. First of all, the transmissibility functions of theundamaged signals and the damage signals at different points are calculated. Secondly,the difference between them is taken as the damage index. Finally, principal componentanalysis (PCA) is used to reduce the noise feature. And then, input to the online sequencelimit learning neural network classification to identify damage and confirm the damagelocation. Taking the amplitude of the transmissibility function instead of the accelerationresponse as the signal analysis for structural damage identification cannot be influencedby the excitation amplitude. The OS-ELM algorithm is based on the ELM (ExtremeLearning Machine) algorithm, in-creased training speed also increases the recognitionaccuracy. Experiment in the epoxy board shows that the method can effectively identifythe structural damage accurately.

关键词： Impact damage transmissibility function OS-ELM

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Coverless Image Steganography Method Based on Feature Selection

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Journal of Information Hiding and Privacy Protection 2019年第2期1卷 49-60页

作者： Anqi Qiu Xianyi Chen Xingming Sun Shuai Wang Guo Wei School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Jiangsu Engineering Centre of Network Monitoring Nanjing210044China Department of Radiology and BRIC University of North Carolina at Chapel HillNorth Carolina27599USA Mathematics and Computer Science University of North Carolina at PembrokeNorth Carolina28372USA

A new information hiding technology named coverless information hiding is *** uses original natural images as stego images to represent secret *** focus of coverless image steganography method is how to represent image features and establish a map relationship between image feature and the secret *** this paper,we use three kinds of features which are Local Binary Pattern(LBP),the mean value of pixels and the variance value of *** this basis,we realize the transmission of secret ***,the hash sequence of the original cover image is obtained according to the description of the feature,and then the sequence of the secret information and the hash sequence of the original cover image are matched one by *** the values are not the same,the image blocks of the original cover image are replaced according to the secret information to get the stego *** paper explores the effect of three features on the visual quality of stego *** results show that the feature LBP is the best.

关键词： Coverless-image-steganography(CIS) feature visual quality.

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Coverless Information Hiding Based on the Molecular Structure Images of Material

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computers, Materials & Continua 2018年第2期54卷 197-207页

作者： Yi Cao Zhili Zhou Xingming Sun Chongzhi Gao 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 AvenueWindsorONCanada N9B 3P4 School of Computer Science Guangzhou UniversityWaihuanxi RoadNo.230Guangzhou510006China

The traditional information hiding methods embed the secret information by modifying the carrier,which will inevitably leave traces of modification on the *** this way,it is hard to resist the detection of steganalysis *** address this problem,the concept of coverless information hiding was *** information hiding can effectively resist steganalysis algorithm,since it uses unmodified natural stego-carriers to represent and convey confidential ***,the state-of-the-arts method has a low hidden capacity,which makes it less *** the pixel values of different regions of the molecular structure images of material(MSIM)are usually different,this paper proposes a novel coverless information hiding method based on MSIM,which utilizes the average value of sub-image’s pixels to represent the secret information,according to the mapping between pixel value intervals and secret *** addition,we employ a pseudo-random label sequence that is used to determine the position of sub-images to improve the security of the *** the histogram of the Bag of words model(BOW)is used to determine the number of subimages in the image that convey secret ***,to improve the retrieval efficiency,we built a multi-level inverted index ***,the proposed method can also be used for other natural *** with the state-of-the-arts,experimental results and analysis manifest that our method has better performance in anti-steganalysis,security and capacity.

关键词： Coverless information hiding molecular structure images of material pixel value inverted index image retrieval bag of words model

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Joint Bayesian guided metric learning for end-to-end face verification

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Neurocomputing 2018年 275卷 560-567页

作者： Di Chen Chunyan Xu Jian Yang Jianjun Qian Yuhui Zheng Linlin Shen School of Computer Science and Engineering Nanjing University of Science and Technology 210094 China Jiangsu Engineering Center of Network Monitoring School of computer and software Nanjing University of Information Science and Technology 210044 China School of Computer Science and Software Engineering Shenzhen University 518060 China

In this work, we address the problem of face verification, namely determining whether a pair of face images belongs to the same or different subjects. Previous works often consider solving the problem of face verification in two steps: feature extraction and face recognition, resulting in a fragmented procedure. We argue that these techniques, although working well, fail to explicitly exploit a full end-to-end framework for face verification, which has received much attention and achieved significant improvements recently. In this paper, we propose a novel Joint Bayesian guided metric learning technique for dealing with the face verification task, which well integrates the above two steps of face verification into an end-to-end convolutional neural network (CNN) architecture. In the training stage, an initial neural network, which has the similar architecture with GoogLeNet CNN model, is firstly pre-trained by optimizing classification-based objective functions on the publicly available CASIA WebFace database. Based on constructed face pairs dataset from CASIA WebFace and LFW datasets, we then fine-tune the whole network parameters under the guide of the learned knowledge, which is obtained from the highly successful Joint Bayesian model. This guided learning procedure, which can also be seen as a metric learning technique, can further update network parameters for discriminating face pairs. In the testing process, the outputs by this unified network are discriminated with a threshold value to produce the ultimate prediction for the face verification task. Comprehensive evaluations over the LFW dataset well demonstrate the encouraging face verification performance of our proposed framework.

关键词： Face verification Convolutional neural network Joint Bayesian model

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Digital continuity guarantee of electronic record based on data usability in big data environment 4th

Digital continuity guarantee of electronic record based on d...

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4th International Conference on Cloud Computing and Security, ICCCS 2018

作者： Xu, Jiang Zhang, Jian Ren, Yongjun Kim, Hye-Jin Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China School of Computer and Software Nanjing University of Information Science and Technology Nanjing China Business Administration Research Institute Sungshin W. University Seoul Korea Republic of

ISBN: (纸本)9783030000059

At present some developed countries have put forward their digital continuity action plans. And the digital continuity has also become a hot spot in the research of electronic records. However, the technology and measures for the protection of the digital continuity are still lack. In this paper, we first point out the necessity of ensuring the availability and completeness of the electronic record. Moreover, the technology framework of availability and completeness for electronic record are firstly proposed. Secondly, we make use of the coding theory to ensure the availability of electronic record. In addition, the technology of ensuring completeness for electronic record is constructed based on functional dependency theory, and the method of evaluating completeness of electronic record is present using the functional dependency theory. © Springer Nature Switzerland AG 2018.

关键词： Big data

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Compressive Sensing Sparse Sampling Method for Composite Material Based on Principal Component Analysis

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Transactions of Nanjing University of Aeronautics and Astronautics 2018年第2期35卷 282-289页

作者： Sun Yajie Gu Feihong Ji Sai Wang Lihua Jiangsu Engineering Centre of Network Monitoring Nanjing University of Information Science and Technology Nanjing 210044 P. R. China Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology Nanjing University of Information Science and Technology Nanjing 210044 P. R. China School of Computer and Software Nanjing University of Information Science and Technology Nanjing 210044 P. R. China School of Information and Control Nanjing University of Information Science and Technology Nanjing 210014 P. R. China

Signals can be sampled by compressive sensing theory with a much less rate than those by traditional Nyquist sampling theorem,and reconstructed with high probability,only when signals are sparse in the time domain or a transform *** signals are not sparse in real world,but can be expressed in sparse form by some kind of sparse *** used sparse transformations will lose some information,because their transform bases are generally *** this paper,we use principal component analysis for data reduction,and select new variable with low dimension and linearly correlated to the original variable,instead of the original variable with high dimension,thus the useful data of the original signals can be included in the sparse signals after dimensionality reduction with maximize ***,the loss of data can be reduced as much as possible,and the efficiency of signal reconstruction can be ***,the composite material plate is used for the experimental *** experimental result shows that the sparse representation of signals based on principal component analysis can reduce signal distortion and improve signal reconstruction efficiency.

关键词： principal component analysis compressive sensing sparse representation signal reconstruction

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An intelligent agent-based method for task allocation in competitive cloud environments

An intelligent agent-based method for task allocation in com...

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作者： Kong, Yan Zhang, Minjie Ye, Dayong Zhu, Jinxiu Choi, Junho Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing210044 China School of Computer Science and Software Engineering University of Wollongong Wollongong2522 Australia Research Institute of Ocean and offshore engineering Hohai Universtiy Nantong226300 China Division of Undeclared Majors Chosun University Gwangju61452 Korea Republic of

In market-based cloud environments, both resource consumers and providers are self-interested;additionally, they can come and leave the environment freely. Therefore, the environment is competitive and uncertain. Because of the competition, participants may cheat in making deals, and this represents that the environment is insecure to resource providers who intend to earn profits through renting their resources to the tasks of resource consumers. Against this, in this paper, intelligent agents are designed to strategically quote for the tasks that they are interested in, on behalf of resource providers. Agents could quote according to the messages it obtained and the information learnt and predicted from the messages, to minimize the influence of insecure factors, such as cheating, competition, and dynamism. The experimental evaluation shows that the proposed method outperforms both a well-known multiresource negotiation-based task allocation method and a max-sum belief propagation–based method. Copyright © 2017 John Wiley & Sons, Ltd.

关键词： Intelligent agents

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