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Cubic medium field equation public key cryptosystem

International Journal of network security 2018年第3期20卷 472-477页

作者： Lu, Gang Xue, Linyuan Nie, Xuyun Qin, Zhiguang Liu, Bo School of Information and Software Engineering University of Electronic Science and Technology of China 4 Jianshe North Rd 2nd Section Chenghua Qu Chengdu610054 China State Key Laboratory of Information Security Institute of Information Engineering Beijing100093 China Network and Data Security Key Laboratory of Sichuan Province Chengdu610054 China

Medium Field Equation (MFE) multivariate public key cryptosystems were broken by High Order Linearization Equation (HOLE) attack. In order to avoid HOLE attack, we proposed an improvement of MFE, Cubic MFE public key encryption scheme. In our construction, multiplications of three second order matrices were used to get a set of cubic polynomials in the central map. Through theoretical analysis and computer experiments, the Cubic MFE is shown to be secure against HOLE attack and other existing attacks. © International Journal of network security.

关键词： Linearization

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A design of the common platform of wireless communication based on FPGA

A design of the common platform of wireless communication ba...

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2017 IEEE Conference on Energy Internet and Energy System Integration, EI2 2017

作者： Qiao, Lei Zheng, Zhe Cui, Wenpeng Zhang, Weilong Jiang, Xueping Research Department of Smart Chip Global Energy Interconnection Research Institute Beijing China State Grid Key Laboratory of Information and Network Security State Grid Laboratory of Electric Power Communication Network Technology Beijing China

ISBN: (纸本)9781538614273

We present a design of the common platform of wireless communication based on FPGA. The platform, developed by us, allows researchers to modify transport protocols on any layer of an OSI reference model, from physical layer to application one, thereby it is feasible to implement multiple wireless communication protocols on different layers. © 2017 IEEE.

关键词： Field programmable gate arrays (FPGA)

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Coarse to fine: Diffusing categories in wikipedia 26

Coarse to fine: Diffusing categories in wikipedia

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26th International World Wide Web Conference, WWW 2017 Companion

作者： Cai, Pengshan Feng, Yansong Jia, Yantao Wang, Yuanzhuo Jin, Xiaolong Cheng, Xueqi CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences Beijing China Institute of Computer Science and Technology Peking University Beijing China

ISBN: (纸本)9781450349147

Automatic taxonomy construction aims to build a categorization system without human efforts. Traditional textual pattern based methods extract hyponymy relation in raw texts. However, these methods usually yield low precision and recall. In this paper, we propose a method to automatically find diffusing attributes to a category from Wikipedia infoboxes. We use the diffusing attribute to diffuse a coarse-grained category into several fine-grained subcategories and generate a finer-grained taxonomy. Experiments show our method can find proper diffusing attributes to categories across various domains. © 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License.

关键词： Taxonomies

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A novel visible-infrared image fusion framework for smart city

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International Journal of Simulation and Process Modelling 2018年第2期13卷 144-155页

作者： Zhu, Zhiqin Qi, Guanqiu Chai, Yi Yin, Hongpeng Sun, Jian School of Automation Chongqing University Chongqing400044 China State Key Laboratory of Power Transmission Equipment and System Security and New Technology College of Automation Chongqing University Chongqing400044 China School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ85287 United States Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing400030 China

Image fusion technology is widely used in different areas and can integrate complementary and relevant information of source images captured by multiple sensors into a unitary synthetic image. Image fusion technology as an efficient way to integrate information from multiple images plays a more and more important role in smart city. The quality of fused image affects the accuracy, efficiency, and robustness of the related applications. Existing sparse representation-based image fusion methods consist of overly complete and redundant dictionaries learning and sparse coding. However, overly complete and redundant dictionary does not consider the discriminative ability of dictionaries that may seriously affect the image fusion. A good dictionary is the key to a successful image fusion technique. To construct a discriminative dictionary, a novel framework that integrates an image-patches clustering and online dictionary learning methods is proposed for visible-infrared image fusion. The comparison experiments with existing solutions are used to validate and demonstrate the effectiveness of the proposed solution for image fusion. Copyright © 2018 Inderscience Enterprises Ltd.

关键词： Image fusion

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Model inconsistent but correlated noise: Multi-view subspace learning with regularized Mixture of Gaussians

arXiv

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arXiv 2018年

作者： Yong, Hongwei Meng, Deyu Li, Jinxing Zuo, Wangmeng Zhang, Lei Department of Computing Hong Kong Polytechnic University Hong Kong Hong Kong School of Mathematics and Statistics Ministry of Education Key Lab of Intelligent Networks and Network Security Xian Jiaotong University School of Computer Science and Technology Harbin Institute of Technology Harbin150001 China

Multi-view subspace learning (MSL) aims to find a low-dimensional subspace of the data obtained from multiple views. Different from single view case, MSL should take both common and specific knowledge among different views into consideration. To enhance the robustness of model, the complexity, non-consistency and similarity of noise in multi-view data should be fully taken into consideration. Most current MSL methods only assume a simple Gaussian or Laplacian distribution for the noise while neglect the complex noise configurations in each view and noise correlations among different views of practical data. To this issue, this work initiates a MSL method by encoding the multi-view-shared and single-view-specific noise knowledge in data. Specifically, we model data noise in each view as a separated Mixture of Gaussians (MoG), which can fit a wider range of complex noise types than conventional Gaussian/Laplacian. Furthermore, we link all single-view-noise as a whole by regularizing them by a common MoG component, encoding the shared noise knowledge among them. Such regularization component can be formulated as a concise KL-divergence regularization term under a MAP framework, leading to good interpretation of our model and simple EM-based solving strategy to the problem. Experimental results substantiate the superiority of our method. Copyright © 2018, The Authors. All rights reserved.

关键词： Signal encoding

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An image encryption algorithm based on compressed sensing and dual-tree complex wavelet transform 17

An image encryption algorithm based on compressed sensing an...

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5th International Conference on Bioinformatics and Computational Biology, ICBCB 2017

作者： Dong, Jiwen Zhao, Ziru Li, Hengjian Department of Computer Science and Technology Shandong Provincial Key Laboratory of Network based Intelligent Computing University of Jinan Jinan City Shandong Province China

ISBN: (纸本)9781450348270

Combined image encryption with the process of compressed sensing (CS) which based on dual-tree complex wavelet transform, we came up with the image encryption algorithm which based on the theory of CS and double random phase encoding (DRPE). Firstly, adopting DT-CWT represent the image sparsely. It can enhance the image edge and texture, it also can attain directional feature information. Secondly, utilizing chaotic system to product chaos sequence as the measurement matrix on the process of CS. At the same time, the values of initial chaotic parameters are the keys. Finally, we selected DRPE on measurements to finish the process of secondary encryption. The values of seeds which are used to generate two random phase masks are the keys of secondary encryption. In the process of decryption, providing the correct values of keys can generate the chaotic measurement matrix and random phase masks to be used for decryption. Orthogonal matching pursuit (OMP) algorithm is employed to reconstruct the original image approximately. Compared with several existing algorithms, this encryption scheme can reconstruct a higher quality image. It has higher robustness and higher sensitivity to the initial keys. © 2017 ACM.

关键词： Cryptography

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Palm-print recognition algorithm based on random projection and chaotic system 17

Palm-print recognition algorithm based on random projection ...

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5th International Conference on Bioinformatics and Computational Biology, ICBCB 2017

作者： Dong, Jiwen Zhao, Ziru Li, Hengjian Feng, Guang Department of Computer Science and Technology Shandong Provincial Key Laboratory of Network based Intelligent Computing University of Jinan Jinan City Shandong Province China

ISBN: (纸本)9781450348270

To improve the efficiency and security of palm-print recognition, we proposed a palm-print algorithm which based on random projection and chaotic system. Using twice random projections based on chaotic system to process the palm-print image, it generated the random project matrix and palm-print which are equivalent to two-factor identity authentications. And the initial value of chaotic system also could be the key to protect the security of palm-print. Reducing the dimensionality of the transformation matrix which could be produced randomly and the transformation matrix was not depend on the original training sample completely. In addition, the process of producing the random project matrix is simple and has lower computational complexity. And users could change the key by regain the new random project matrix to protect their privacy. © 2017 ACM.

关键词： Palmprint recognition

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Image Classification Based on Quantum KNN Algorithm

arXiv

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arXiv 2018年

作者： Dang, Yijie Jiang, Nan Hu, Hao Ji, Zhuoxiao Zhang, Wenyin Faculty of Information Technology Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Trusted Computing Beijing100124 China National Engineering Laboratory for Critical Technologies of Information Security Classified Protection Beijing100124 China School of Information Science and Technology Linyi University Linyi276000 China

Image classification is an important task in the field of machine learning and image processing. However, the usually used classification method — the K Nearest-Neighbor algorithm has high complexity, because its two main processes: similarity computing and searching are time-consuming. Especially in the era of big data, the problem is prominent when the amount of images to be classified is large. In this paper, we try to use the powerful parallel computing ability of quantum computers to optimize the efficiency of image classification. The scheme is based on quantum K Nearest-Neighbor algorithm. Firstly, the feature vectors of images are extracted on classical computers. Then the feature vectors are inputted into a quantum superposition state, which is used to achieve parallel computing of similarity. Next, the quantum minimum search algorithm is used to speed up searching process for similarity. Finally, the image is classified by quantum measurement. The complexity of the quantum algorithm is only O(√kM), which is superior to the classical algorithms. Moreover, the measurement step is executed only once to ensure the validity of the scheme. The experimental results show that, the classification accuracy is 83.1% on Graz-01 dataset and 78% on Caltech-101 dataset, which is close to existing classical algorithms. Hence, our quantum Copyright © 2018, The Authors. All rights reserved.

关键词： Image classification

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Chinese Herbal Medicine Classification Using Convolutional Neural network with Multiscale Images and Data Augmentation

Chinese Herbal Medicine Classification Using Convolutional N...

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International Conference on security, Pattern Analysis, and Cybernetics (SPAC)

作者： Tianhao Li Fengyang Sun Runyuan Sun Lin Wang Meihui Li Huawei Yang Shandong Provincial Key Laboratory of Network based Intelligent Computing University of Jinan Jinan China Shandong Provincial Key Laboratory of of Oral Tissue Regeneration Shandong University Jinan Shandong China Jinan Kingmon Information Technology Co. Ltd. Jinan China

ISBN: (纸本)9781728105529

Correct use of Chinese herbal medicines is vital to life safety of the patients. Chinese herbal medicine classification is very important for the correct use of Chinese herbal medicines. Traditional methods like microfeature identification and physiochemical identification are inefficient due to the various kinds and different conditions of Chinese herbal medicines. Therefore, we adopt a multiscale convolutional neural network (CNN) model with data augmentation technology to classify Chinese herbal medicines. The data augmentation techniques solve the problem of less data on Chinese herbal medicines. Multiscale technology extracts more useful features for Chinese herbal medicine classification. The experiments show favorable accuracy.

关键词： Chinese herbal medicine Convolutional neural network Data augmentation Multiscale chinese herbal medicine Feature extraction

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An Event Timeline Extraction Method Based on News Corpus 2

An Event Timeline Extraction Method Based on News Corpus

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2017 IEEE 2nd International Conference on Big Data Analysis（ICBDA 2017）

作者： Yaguang Wu Haichun Sun Chungang Yan Department of Computer Science and Technology Tongji University The Key Laboratory of Embedded System and Service Computing Tongji University College of Police Information Engineering People's Public Security University of China

ISBN: (纸本)9781509036202

Event extraction is an important research point in information extraction area, and news event extraction has a greater practical significance. The existing methods of extracting news event, which starts from the time element, is to identify the date sentences hold by Natural Language Processing and extract the event on the date by Text Clustering. However, they only process the news that holds a time-tag and gives up the news that has no accurate date, which easily leads an extraction deviation of significant events and reduces the accuracy of ordering the significant events. In this paper, improvement for this defect is to calculate the similarities between sentences to put part of the non-time-tag sentences into the right date container, thereby the accuracy of ordering the significant event is *** experiments and compared with the existing methods,the accuracy of ordering the significant events in this paper is improved by 14.6%.

关键词： event extraction text information mining sentence similarity timeline

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