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A Privacy-Preserving Image Retrieval Based on AC-Coefficients and Color Histograms in Cloud Environment

computers, Materials & Continua 2019年第1期58卷 27-43页

作者： Zhihua Xia Lihua Lu Tong Qiu H.J.Shim Xianyi Chen Byeungwoo Jeon Jiangsu Engineering Centre of Network Monitoring Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment TechnologySchool of Computer and SoftwareNanjing University of Information Science&TechnologyNanjing210044China College of Information&Communication Engineering Sungkyunkwan UniversityKorea

Content based image retrieval(CBIR)techniques have been widely deployed in many applications for seeking the abundant information existed in *** to large amounts of storage and computational requirements of CBIR,outsourcing image search work to the cloud provider becomes a very attractive option for many owners with small ***,owing to the private content contained in images,directly outsourcing retrieval work to the cloud provider apparently bring about privacy problem,so the images should be protected carefully before *** paper presents a secure retrieval scheme for the encrypted images in the YUV color *** this scheme,the discrete cosine transform(DCT)is performed on the Y *** resulting DC coefficients are encrypted with stream cipher technology and the resulting AC coefficients as well as other two color components are encrypted with value permutation and position *** the image owner transmits the encrypted images to the cloud *** receiving a query trapdoor form on query user,the server extracts AC-coefficients histogram from the encrypted Y component and extracts two color histograms from the other two color *** similarity between query trapdoor and database image is measured by calculating the Manhattan distance of their respective ***,the encrypted images closest to the query image are returned to the query user.

关键词： Image retrieval AC-coefficients histogram color histogram discrete cosine transform

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A Survey of Image Super Resolution Based on CNN 9th

A Survey of Image Super Resolution Based on CNN

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9th EAI International Conference on Cloud Computing, CloudComp 2019 and the 4th EAI International Conference on Smart Grid and Innovative Frontiers in Telecommunications, SmartGIFT 2019

作者： Xu, Qianxiong Zheng, Yu School of Computer and Software Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology NanjingJiangsu210044 China

ISBN: (纸本)9783030485122

With the advent of the information age in contemporary society, images are everywhere, no matter in military use or in daily life. Therefore, as a medium for people to obtain information, images have become more and more important. With the fast development of deep convolution neural networks (DCNNs), Single-Image Super-Resolution (SISR) becomes one of the techniques that have made great breakthroughs in recent years. In this paper, we give a brief survey on the task of SISR. In general, we introduce the SR problem, some recent SR methods, public benchmark datasets and evaluation metrics. Finally, we conclude by denoting some points that could be further improved in the future. © 2020, ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Surveys

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An enhanced grouping proof for multiple rfid readers and tag groups

International Journal of Control and Automation

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International Journal of Control and Automation 2014年第12期7卷 239-246页

作者： Shen, Jian Tan, Haowen Wang, Yang Ji, Sai Wang, Jin Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing China Jiangsu Technology and Engineering Center of Meteorological Sensor Network Nanjing University of Information Science and Technology Nanjing China School of Computer and Software Nanjing University of Information Science and Technology Nanjing China

RFID authentication on large numbers of tags or tag groups has attracted many researchers' attention as an extension of initial one-or-two-tags scenarios. Due to demands of RFID application in supply chain, various proofs are proposed in the purpose of solving existing problems of grouping tags identification. However, it is proved that verifiers in these proofs are not aware of abnormal relating devices instantly, which may cause both security and technical risks and lie heavy upon identification of the problematic tags and readers. In this paper, we propose an enhanced grouping proof for multiple RFID readers and tag groups, according to which the verifier is able to cope with multiple readers and tag groups simultaneously and know the detailed status of the problematic tags. In addition, privacy protection is provided by offering mutual authentication between the readers and tags. Moreover, it is hard for the malicious tags to pass the verification in the proposed proof. © 2014 SERSC.

关键词： Supply chains

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A GLCM-Feature-Based Approach for Reversible Image Transformation

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computers, Materials & Continua 2019年第4期59卷 239-255页

作者： Xianyi Chen Haidong Zhong Zhifeng Bao School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Jiangsu Engineering Centre of Network Monitoring Nanjing210044China School of Computer Science and Information Technology RMIT UniversityMelbourneAustralia

Recently,a reversible image transformation(RIT)technology that transforms a secret image to a freely-selected target image is *** not only can generate a stego-image that looks similar to the target image,but also can recover the secret image without any *** also has been proved to be very useful in image content protection and reversible data hiding in encrypted ***,the standard deviation(SD)is selected as the only feature during the matching of the secret and target image blocks in RIT methods,the matching result is not so good and needs to be further improved since the distributions of SDs of the two images may be not very ***,this paper proposes a Gray level co-occurrence matrix(GLCM)based approach for reversible image transformation,in which,an effective feature extraction algorithm is utilized to increase the accuracy of blocks matching for improving the visual quality of transformed image,while the auxiliary information,which is utilized to record the transformation parameters,is not ***,the visual quality of the stego-image should be *** results also show that the root mean square of stego-image can be reduced by 4.24%compared with the previous method.

关键词： Image encryption feature extraction reversible image transformation GLCM

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Quantum Algorithms and Experiment Implementations Based on IBM Q

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computers, Materials & Continua 2020年第11期65卷 1671-1689页

作者： Wenjie Liu Junxiu Chen Yinsong Xu Jiahao Tang Lian Tong Xiaoyu Song Jiangsu Engineering Center 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 Engineering Jiangsu Maritime InstituteNanjing211100China Department of Electrical and Computer Engineering Portland State UniversityOregon97207USA

With the rapid development of quantum theory and technology in recent years,especially the emergence of some quantum cloud computing platforms,more and more researchers are not satisfied with the theoretical derivation and simulation verification of quantum computation(especially quantum algorithms),experimental verification on real quantum devices has become a new *** this paper,three representative quantum algorithms,namely Deutsch-Jozsa,Grover,and Shor algorithms,are briefly depicted,and then their implementation circuits are presented,*** program these circuits on python with QISKit to connect the remote real quantum devices(i.e.,ibmqx4,ibmqx5)on IBM Q to verify these *** experimental results not only show the feasibility of these algorithms,but also serve to evaluate the functionality of these devices.

关键词： Quantum algorithms implementation circuit IBM Q QISKit program

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A significance-driven framework for characterizing and finding evolving patterns of news networks

A significance-driven framework for characterizing and findi...

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4th International Conference on Artificial Intelligence and Computational Intelligence, AICI 2012

作者： Yan, Leiming Wang, Jinwei Han, Jin Wang, Yuxiang School of Computer and Software Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing 210044 China

ISBN: (纸本)9783642334771

Social network analysis has become extremely popular in recent years. What are the most significant evolving behaviors in a social network? It is very difficult to find significant evolving behaviors from a large network in a long evolving time interval. Besides, verifying and evaluating enormous dynamic patterns extracted from a large social network by experts are also too hard to generalize well. In this work, a significance-driven framework is proposed to characterize the evolution of local topology and find dynamic patterns with evidently statistical significance for temporally varying news report networks. Two significance indices-potential index and evolving score are introduced for evaluating evolving patterns. Finally, we present a systematic analysis of one real news network, which demonstrates that the method we proposed can find the evolving characteristic and extract significant dynamic patterns from news networks. © 2012 Springer-Verlag.

关键词： computers

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Partial-duplicate image retrieval using spatial and visual contextual clues

Partial-duplicate image retrieval using spatial and visual c...

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作者： Sun, Wendi Wang, Tao Zhou, Zhili School of Computer and Software and Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing210044 China

The traditional bag-of-visual-words (BOW) model quantifies the local features to the visual words to achieve efficient content-based image retrieval. However, since it causes considerable quantisation error and ignores the spatial relationships between visual words, the accuracy of partial-duplicate image retrieval based on BOW model is limited. In order to reduce the quantisation error and improve the discriminability of visual words, many partial-duplicate image retrieval methods have been proposed, which make use of the advantages of the geometric clues between visual words. In this paper, we propose a novel partial-duplicate scheme by using both spatial and visual contextual clues for removing the false matches effectively, which not only encodes the relationships of orientation, distance and dominant orientation between the referential visual word and its context, but also takes the colour information between visual words into consideration. Experimental results reveal that our proposed algorithm achieves superior performance to the state-of-the-art methods for partial-duplicate image retrieval. Copyright © 2020 Inderscience Enterprises Ltd.

关键词： Image enhancement

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Secure storage of data in cloud computing 10

Secure storage of data in cloud computing

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10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014

作者： Fu, Zhangjie Cao, Xinyue Wang, Jin Sun, Xingming School of Computer and Software and Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing210044 China

ISBN: (纸本)9781479953905

Cloud storage brings convenient storage of data, at the same time there are also hidden security issues. Data storage security includes legal access to the data stored in the cloud, namely access authorization and authentication security data sharing and the encryption of stored data to ensure data confidentiality, consisting of the accessibility to effective cryptographic data and inaccessibility to the deleted cryptographic data, using tamper-proof technology to ensure the integrity of the data, as well as using tracking technology to ensure data traceability. This paper focuses on the file systems with secure data deletion. We design a file system which supports secure deletion of data. It uses CP-ABE which supports fine-grained access policy to encrypt files. © 2014 IEEE.

关键词： Cloud storage

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Data access control for multi-authority cloud storage systems

Data access control for multi-authority cloud storage system...

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10th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2014

作者： Fu, Zhangjie Xin, Lin Wang, Jin Sun, Xingming School of Computer and Software and Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science and Technology Nanjing 210044 China

ISBN: (纸本)9781479953905

Ciphertext-Policy Attribute-based Encryption (CP-ABE) is one of the most suitable technologies for data access control in cloud storage systems. This paper firstly presents the Attribute-based Encryption (ABE), secure deletion and secret-sharing schemes. Then we construct a CP-ABE model using secret-sharing methods to insure its security. At last, we propose an improved scheme on Data Access Control for Multi-Authority Cloud Storage Systems DAC-MACS to insure the security of the central authority (CA). © 2014 IEEE.

关键词： Access control

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Improved locality-sensitive hashing method for the approximate nearest neighbor problem

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Chinese Physics B 2014年第8期23卷 217-225页

作者：陆颖华马廷淮钟水明曹杰王新 Abdullah Al-Dhelaane Jiangsu Engineering Center of Network Monitoring Nanjing University of Information Science & Technology School of Computer & Software Nanjing University of Information Science & Technology School of Economic & Management Nanjing University of Information Science & Technology Huafeng Meteorological Media Group Computer Science Department College of Computer and Information Science King Saud University

In recent years, the nearest neighbor search （NNS） problem has been widely used in various interesting applications. Locality-sensitive hashing （LSH）, a popular algorithm for the approximate nearest neighbor problem, is proved to be an efficient method to solve the NNS problem in the high-dimensional and large-scale databases. Based on the scheme of p-stable LSH, this paper introduces a novel improvement algorithm called randomness-based locality-sensitive hashing （RLSH） based on p-stable LSH. Our proposed algorithm modifies the query strategy that it randomly selects a certain hash table to project the query point instead of mapping the query point into all hash tables in the period of the nearest neighbor query and reconstructs the candidate points for finding the nearest neighbors. This improvement strategy ensures that RLSH spends less time searching for the nearest neighbors than the p-stable LSH algorithm to keep a high recall. Besides, this strategy is proved to promote the diversity of the candidate points even with fewer hash tables. Experiments are executed on the synthetic dataset and open dataset. The results show that our method can cost less time consumption and less space requirements than the p-stable LSH while balancing the same recall.

关键词： approximate nearest neighbor problem locality-sensitive hashing

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