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SSEM： Secure, Scalable and Efficient Multi-Owner Data Sharing in Clouds

China Communications 2016年第8期13卷 231-243页

作者： Shungan Zhou Ruiying Du Jing Chen Hua Deng Jian Shen Huanguo Zhang The Key Laboratory of Aerospace Information Security and Trusted Computing Ministry of Education Computer School of Wuhan University Wuhan 430072 Hubei Province China State Grid Information and Communication Company of Hunan Electric Power Corp Changsha 410000 Hunan Province China

Data sharing is a main application of cloud computing. Some existing solutions are proposed to provide flexible access control for outsourced data in the cloud. However, few attentions have been paid to group-oriented data sharing when multiple data owners want to share their private data for cooperative purposes. In this paper, we put forward a new paradigm, referred to as secure, scalable and efficient multi-owner(SSEM) data sharing in clouds. The SSEM integrates identity-based encryption and asymmetric group key agreement to enable group-oriented access control for data owners in a many-to-many sharing pattern. Moreover, with SSEM, users can join in or leave from the group conveniently with the privacy of both group data and user *** proposed the key-ciphertext homomorphism technique to construct an SSEM scheme with short ciphertexts. The security analysis shows that our SSEM scheme achieves data security against unauthorized accesses and collusion attacks. Both theoretical and experimental results confirm that our proposed scheme takes users little costs to share and access outsourced data in a group manner.

关键词： data sharing cloud computing asymmetric key agreement access control

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Exploiting Meta-Path with Attention Mechanism for Fine-Grained User Location Prediction in LBSNs

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Journal of Physics: Conference Series 2019年第1期1284卷

作者： Zhixiao Wang Wenyao Yan Wendong Wang Ang Gao Lei Yu Shaobo Yang GaoYang Nie School of Computer Science and Engineering Xi'an University of Technology 710048 Xi'an China Telematics Group the University of Goettingen 37077 Goettingen Germany Shaanxi Key Laboratory of Network Computing and Security 710048 Xi'an China School of Electronic and Information Engineering Xi'an Jiaotong University 710048 Xi'an China College of Xi'an Innovation Yan'an University 710100 Xi'an China Yan'an University Yan'an 716000 China National Satellite Meteorological Center China Meteorological Administration Beijing 100081 China

Based on the huge volumes of user check-in data in LBSNs, users' intrinsic mobility patterns can be well explored, which is fundamental for predicting where a user will visit next given his/her historical check-in records. As there are various types of nodes and interactions in LBSNs, they can be treated as Heterogeneous information network (HIN) where multiple semantic meta-paths can be extracted. Inspired by the recent success of meta-path context based embedding techniques in HIN, in this paper, we design a deep neural network framework leveraging various meta-path contexts for fine-grained user location prediction. Experimental results based on two real-world LBSN datasets demonstrate the best effectiveness of the proposed approach using various evaluation metrics than others.

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Multiple influence maximization in social networks 10

Multiple influence maximization in social networks

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10th International Conference on Ubiquitous information Management and Communication, IMCOM 2016

作者： Sun, Honglin Gao, Xiaofeng Chen, Guihai Gu, Jian Wang, Yongjian Shanghai Key Lab. of Scalable Computing and Systems Dept. of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory of Information Network Security of Ministry of Public Security Third Research Institute of Ministry of Public Security Shanghai China

ISBN: (纸本)9781450341424

Influence Maximization, a technique of social analysis to help marketers select a small group of users to promote their products with the goal of maximizing their influence spread, has been studied for a long time. However, previous researches did not consider the scenario that a company may intend to promote serval kinds of products in the same social network, where each user has different preferences for different categories. Considering this scenario in this paper, we propose the Multiple Influence Maximization (MIM) problem based on the assumption that one seed user can accept serval kinds of goods for free, and at the same time non-seed users have enough purchasing power to accept different promotions from their social friends. To address this issue, we design the corresponding greedy algorithm framework with an approximate radio of 1-1/e if the influence function is submodular. Besides, to simplify the computation of influence spread and considering the properties of real social influence propagation, we propose a novel influence quantitative computation model in which influence function fortunately is submodular. Applying this model into our MIM problem, the experiment results show that the greedy algorithm out-performs serval traditional heuristics in influence spread without loss of performance. © 2015 ACM.

关键词： Method of moments

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Robust Multi-Exposure Image Fusion: A Structural Patch Decomposition Approach

Robust Multi-Exposure Image Fusion: A Structural Patch Decom...

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作者： Ma, Kede Li, Hui Yong, Hongwei Wang, Zhou Meng, Deyu Zhang, Lei Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Computing Hong Kong Polytechnic University Hong Kong Hong Kong Department of Computing. Hong Kong Polytechnic University Hong Kong Hong Kong Institute for Information and System Sciences and Ministry of Education Key Laboratory of Intelligent Networks and Network Security Xi'an Jiaotong University Xi'an710049 China Inst. for Info. and Syst. Sci. and Min. of Educ. Key Lab. of Intelligent Networks and Netwk. Secty. Xi'an Jiaotong University Xi'an710049 China

We propose a simple yet effective structural patch decomposition approach for multi-exposure image fusion (MEF) that is robust to ghosting effect. We decompose an image patch into three conceptually independent components: signal strength, signal structure, and mean intensity. Upon fusing these three components separately, we reconstruct a desired patch and place it back into the fused image. This novel patch decomposition approach benefits MEF in many aspects. First, as opposed to most pixel-wise MEF methods, the proposed algorithm does not require post-processing steps to improve visual quality or to reduce spatial artifacts. Second, it handles RGB color channels jointly, and thus produces fused images with more vivid color appearance. Third and most importantly, the direction of the signal structure component in the patch vector space provides ideal information for ghost removal. It allows us to reliably and efficiently reject inconsistent object motions with respect to a chosen reference image without performing computationally expensive motion estimation. We compare the proposed algorithm with 12 MEF methods on 21 static scenes and 12 deghosting schemes on 19 dynamic scenes (with camera and object motion). Extensive experimental results demonstrate that the proposed algorithm not only outperforms previous MEF algorithms on static scenes but also consistently produces high quality fused images with little ghosting artifacts for dynamic scenes. Moreover, it maintains a lower computational cost compared with the state-of-The-Art deghosting schemes.11The MATLAB code of the proposed algorithm will be made available online. Preliminary results of Section III-A [1] were presented at the IEEE International Conference on Image Processing, Canada, 2015. © 1992-2012 IEEE.

关键词： Image fusion

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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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IEEE Conference on Energy Internet and Energy System Integration

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

ISBN: (纸本)9781538614280

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.

关键词： Wireless communication OFDM FPGA

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Performance analysis of parallel replica molecular dynamics

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AIP Conference Proceedings 2018年第1期1978卷

作者： Boyao Zhang Jue Wang Yangde Feng Ji Xiang Lei Wang 1Computer Network Information Center Chinese Academy of Science Department of High Performance Computing Technology and Application Development Beijing China 2University of Chinese Academy of Sciences Beijing China 3State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences China 4School of cybersecurity Chinese Academy of Sciences China

Molecular dynamics simulation is an important tool for studying materials microstructure evolution under radiation effects. It is difficult to simulate atomic diffusion in materials owing to the time-scale limitations of the molecular dynamics method. Accelerated molecular dynamics has been developed as a solution and the parallel replica method is the simplest and most accurate of the accelerated dynamics techniques. The simulation time scale can reach several orders more than the direct molecular dynamics, while retaining the complete atomic detail. In parallel replica method, the entire system is replicated on each of M available parallel or distributed processors, it is in line with the characteristics of high-performance parallel computing and can be optimized from the program level.

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Strongly average-case secure obfuscation: achieving input privacy and circuit obscurity

Strongly average-case secure obfuscation: achieving input pr...

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作者： Zhang, Mingwu Mu, Yi Shen, Jian Huang, Xinyi School of Computer Science Hubei University of Technology Wuhan430068 China School of Computer and Software Nanjing University of Information Science and Technology Nanjing China Fujian Provincial Key Laboratory of Network Security and Cryptology Fujian Normal University China School of Computing and Information Technology University of Wollongong NSW2522 Australia

A program obfuscator is a compiling algorithm that takes a program/circuit as input and generates a new garbled circuit to implement the same functionality as before while obtaining hard-to-understand in some sense, that is, infeasible to learn information from the garbled circuit. In order to obtain a practical application, an obfuscation should satisfy equivalent in functionality, polynomial slowdown in efficiency, and virtual black-box in security. In this paper, we model a stronger cryptographic obfuscation that does not only achieves the obfuscated circuit obscurity but also supports input re-key privacy. In order to implement the re-encryption obfuscation, we at first propose a key-privacy two-level encryption mechanism that implicitly supports the transformation from level-2 ciphertext into level-1 one, which provides an efficient method to re-encrypt the ciphertext without explicitly decryption procedure. Under the mechanism of two-level encryption and function of re-encryption, we construct an obfuscation of re-encryption that takes as input a probabilistic (keys) circuit and outputs a transformed circuit. We also give the proof that the obfuscator achieves the average-case security for the circuit family under the extended DBDH assumption and Decisional Linear assumption in the standard model. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

关键词： Timing circuits

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Learning to segment with image-level annotations

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Pattern Recognition 2016年 59卷 234-244页

作者： Wei, Yunchao Liang, Xiaodan Chen, Yunpeng Jie, Zequn Xiao, Yanhui Zhao, Yao Yan, Shuicheng Institute of information Science Beijing Jiaotong University Beijing 100044 China Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing 100044 China School of Advanced Computing Sun Yat-Sen University Guangzhou 510006 China Vision and Machine Learning Lab National University of Singapore 117583 Singapore People׳s Public Security University of China Beijing 100038 China

Recently, deep convolutional neural networks (DCNNs) have significantly promoted the development of semantic image segmentation. However, previous works on learning the segmentation network often rely on a large number of ground-truths with pixel-level annotations, which usually require considerable human effort. In this paper, we explore a more challenging problem by learning to segment under image-level annotations. Specifically, our framework consists of two components. First, reliable hypotheses based localization maps are generated by incorporating the hypotheses-aware classification and cross-image contextual refinement. Second, the segmentation network can be trained in a supervised manner by these generated localization maps. We explore two network training strategies for achieving good segmentation performance. For the first strategy, a novel multi-label cross-entropy loss is proposed to train the network by directly using multiple localization maps for all classes, where each pixel contributes to each class with different weights. For the second strategy, the rough segmentation mask can be inferred from the localization maps, and then the network is optimized based on the single-label cross-entropy loss with the produced masks. We evaluate our methods on the PASCAL VOC 2012 segmentation benchmark. Extensive experimental results demonstrate the effectiveness of the proposed methods compared with the state-of-the-arts. © 2016 Elsevier Ltd

关键词： Deep learning Semantic segmentation Weakly supervised

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Robust low-rank tensor factorization by cyclic weighted median

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Science China(information Sciences) 2015年第5期58卷 145-155页

作者： MENG DeYu ZHANG Biao XU ZongBen ZHANG Lei GAO ChenQiang Institute for Information and System Sciences and Ministry of Education Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Department of Computing Hong Kong Polytechnic University Chongqing Key Laboratory of Signal and Information Processing Chongqing University of Posts and Telecommunications

Low-rank tensor factorization(LRTF) provides a useful mathematical tool to reveal and analyze multi-factor structures underlying data in a wide range of practical applications. One challenging issue in LRTF is how to recover a low-rank higher-order representation of the given high dimensional data in the presence of outliers and missing entries, i.e., the so-called robust LRTF problem. The L1-norm LRTF is a popular strategy for robust LRTF due to its intrinsic robustness to heavy-tailed noises and outliers. However, few L1-norm LRTF algorithms have been developed due to its non-convexity and non-smoothness, as well as the high order structure of data. In this paper we propose a novel cyclic weighted median(CWM) method to solve the L1-norm LRTF problem. The main idea is to recursively optimize each coordinate involved in the L1-norm LRTF problem with all the others fixed. Each of these single-scalar-parameter sub-problems is convex and can be easily solved by weighted median filter, and thus an effective algorithm can be readily constructed to tackle the original complex problem. Our extensive experiments on synthetic data and real face data demonstrate that the proposed method performs more robust than previous methods in the presence of outliers and/or missing entries.

关键词： tensor factorization low-rank weighted median filter tensorface

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Some classes of complete permutation polynomials over Fq

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Science China Mathematics 2015年第10期58卷 2081-2094页

作者： WU GaoFei LI Nian HELLESETH Tor ZHANG YuQing State Key Laboratory of Integrated Service Networks Xidian University Information Security and National Computing Grid Laboratory Southwest Jiaotong University Department of Informatics University of Bergen National Computer Network Intrusion Protection Center University of Chinese Academy of Sciences

By using a powerful criterion for permutation polynomials, we give several classes of complete permutation polynomials over finite fields. First, two classes of complete permutation monomials whose exponents are of Niho type are presented. Second, for any odd prime p, we give a sufficient and necessary condition for a-1xdto be a complete permutation polynomial over Fp4 k, where d =(p4k-1)/(pk-1)+ 1 and a ∈ F*p4k. Finally, we present a class of complete permutation multinomials, which is a generalization of recent work.

关键词： finite field complete permutation polynomials Walsh transform Niho exponents Dickson polynomials

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