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2nd IEEE Advanced Information Management, Communicates, Electronic and Automation Control Conference, IMCEC 2018

作者： Hassan, Muhammad Umair Shaukat, Kamran Niu, Dongmie Mahreen, Sundas Ma, Yingjun Zhao, Xiuyang Shabir, Muhammad Ahmad University of Jinan Shandong Provincial Key Laboratory of Network Based Intelligent Computing Jinan250022 China Department of Information Technology University of the Punjab Jhelum Campus Jhelum Pakistan

ISBN: (纸本)9781538618035

W384 Mining is defined as the use of Data Mining techniques to extract information from web, automatically. Web Mining techniques are widely used to observe user patterns accessing the web server logs. Web logs are the entries of different users accessing different topics on the web and observed by web server. In this paper, the patterns are extracted from educational institute's website and observed by using WEKA tool. The number of visitors and hits and the bandwidth used by the users are all determined with different perspectives. This work is done to analyze user's behavior and their interests that will be used to predict the future patterns of the website. © 2018 IEEE.

关键词： Websites

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

Exploiting Meta-Path with Attention Mechanism for Fine-Grain...

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2019 3rd International Conference on Data Mining, Communications and Information technology (DMCIT 2019)

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 Telematics Group the University of Goettingen Shaanxi Key Laboratory of Network Computing and Security School of Electronic and Information Engineering Xi'an Jiaotong University College of Xi'an Innovation Yan'an University Yan'an University National Satellite Meteorological Center China Meteorological Administration

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 *** 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 *** 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 *** 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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Multi-criteria collaborative filtering based on matrix filling 4

Multi-criteria collaborative filtering based on matrix filli...

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4th IEEE International Conference on Computer and Communications, ICCC 2018

作者： Ye, Li Wu, Chunming Qiang, Baohua Xie, Wu College of Computer Information Science Southwest University Chongqing China Guangxi Key Laboratory of Cryptography and Information Security Guilin University of Electronic Technology Guilin China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex System Guilin University of Electronic Technology Guilin China

ISBN: (纸本)9781538683392

In multi-criteria collaborative filtering, the data sparsity is a critical factor affecting the effectiveness of the algorithm. Existing solutions generally remove low-efficiency data through dimensionality reduction, decomposition, etc. While at lower data dimension, they also lose original data information, which impacts the accuracy of predicted ratings. This paper adopts a new processing strategy and proposes to use the matrix filling method to handle the missing data. Firstly, an improved similarity algorithm combined with the Jaccard Similarity Coefficient is used to calculate the predicted rating. Secondly, the Reliable Factor is introduced to prevent the error of filling data. Finally, multiple linear regression is employed for aggregating the ratings of the criteria to eventually yield preferred predicted ratings. A series of experiments show that the proposed method can precisely reflect the user's similarity and achieve better results in predicted ratings, in contrast to traditional methods. © 2018 IEEE.

关键词： Collaborative filtering

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Beam-Domain Secret key Generation for Multi-User Massive MIMO networks

arXiv

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arXiv 2020年

作者： Chen, You Li, Guyue Sun, Chen Zhang, Junqing Jorswieck, Eduard Xiao, Bin School of Cyber Science and Engineering Southeast University Nanjing210096 China National Mobile Communications Research Laboratory Southeast University Nanjing210096 China Purple Mountain Laboratories for Network and Communication Security Nanjing210096 China Department of Electrical Engineering and Electronics University of Liverpool LiverpoolL69 3GJ United Kingdom Institute for Communications Technology Technische Universität Braunschweig Germany Department of Computing Hong Kong Polytechnic University Hong Kong

Physical-layer key generation (PKG) in multi-user massive MIMO networks faces great challenges due to the large length of pilots and the high dimension of channel matrix. To tackle these problems, we propose a novel massive MIMO key generation scheme with pilot reuse based on the beam domain channel model and derive close-form expression of secret key rate. Specifically, we present two algorithms, i.e., beam-domain based channel probing (BCP) algorithm and interference neutralization based multi-user beam allocation (IMBA) algorithm for the purpose of channel dimension reduction and multi-user pilot reuse, respectively. Numerical results verify that the proposed PKG scheme can achieve the secret key rate that approximates the perfect case, and significantly reduce the dimension of the channel estimation and pilot overhead. Copyright © 2020, The Authors. All rights reserved.

关键词： Cryptography

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An attribute-based encryption scheme with LSSS key-policy from lattices

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and computing 2018年 613卷 217-230页

作者： Liu, Lihua Wang, Shangping Shaanxi Key Laboratory for Network Computing and Security Technology Xi’an University of Technology Xi’an710054 China School of Mathematics and Computer Science Shaanxi University of Technology HanzhongShaanxi723001 China

ISBN: (纸本)9783319607436

A new attribute-based encryption scheme (ABE) from lattices with Linear Secret Sharing Scheme (LSSS) key-policy is presented. In the new scheme, the key of an attribute under an access policy represented by LSSS is generated by the use of the sample-pre algorithm on lattices. Every attribute has its own authority, and the private key of each attribute under an access policy is produced by its own authority alone. The new scheme has the advantage of fine-grained access control, and also could support multi-authority attribute management, thus it facilitates the practical management of attribute encryption system. The security of the new scheme is proved in the selective-attribute attack model under learning with errors (LWE) assumption, and the security parameter selecting is discussed in detail. © 2018, Springer International Publishing AG.

关键词： Access control

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On self-duality and hulls of cyclic codes over 2m[u]huki with oddly even length

arXiv

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arXiv 2019年

作者： Cao, Yonglin Cao, Yuan Fu, Fang-Wei School of Mathematics and Statistics Shandong University of Technology Zibo Shandong255091 China Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering Changsha University of Science and Technology Changsha Hunan410114 Hubei Key Laboratory of Applied Mathematics Faculty of Mathematics and Statistics Hubei University Wuhan430062 Chern Institute of Mathematics and Lpmc Tianjin Key Laboratory of Network and Data Security Technology Nankai University Tianjin300071 China

Let F2m be a finite field of 2m elements, and R = F2m[u]/huki = 2m + u2m + . . . + uk-1F2m (uk = 0) where k is an integer satisfying k ≥ 2. For any odd positive integer n, an explicit representation for every self-dual cyclic code over R of length 2n and a mass formula to count the number of these codes are given first. Then a generator matrix is provided for the self-dual and 2-quasi-cyclic code of length 4n over F2m derived by every self-dual cyclic code of length 2n over 2m + u2m and a Gray map from 2m + u2m onto F22 m. Finally, the hull of each cyclic code with length 2n over F2m +uF2m is determined and all distinct self-orthogonal cyclic codes of length 2n over 2m + u2m are listed. Copyright © 2019, The Authors. All rights reserved.

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Multidimensional particle swarm optimization based long short-term memory method for human activity recognition 4

Multidimensional particle swarm optimization based long shor...

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4th IEEE International Conference on Computer and Communications, ICCC 2018

作者： Zuo, Peiliang Li, Haoliang Zhang, Yuanli Yang, Tao Ministry of Education Beijing University of Posts and Telecommunications Key Laboratory of Universal Wireless Communication Beijing China Department of Network Space Security Beijing Electronic Science and Technology Institute Beijing China

ISBN: (纸本)9781538683392

Human activity recognition (HAR) is indispensable for human-machine interaction. Related applications in many fields, e.g. medical, military, and security, facilitate and even change the lives of human beings. However, a key issue, i.e. the unsatisfactory recognition accuracy, still remains to be addressed. In this paper, we explore a new way to design a long short-term memory (LSTM) method specifically for HAR with datasets collected by sensors or mobile devices. In particular, combining with the multidimensional particle swarm optimization (MD-PSO), the LSTM method, which has advantages in processing collected datasets with timing characteristics, is not only optimized in terms of parameters (i.e. weights and bias), but also of the network topology as well as the number of blocks in each layer. In other words, we can further get the optimal topology and network mapping parameters of the LSTM network under the conditions of supervised learning. By utilizing the real dataset, performance of the proposed method is verified. Moreover, the test results show that our method significantly outperforms the commonly used support vector machine (SVM) and LSTM methods. © 2018 IEEE.

关键词： Support vector machines

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Quantum and classical query complexities for generalized Simon’s problem

arXiv

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arXiv 2019年

作者： Wu, Zhenggang Qiu, Daowen Tan, Jiawei Li, Hao Cai, Guangya Institute of Quantum Computing and Computer Theory School of Computer Science and Engineering Sun Yat-sen University Guangzhou510006 China The Guangdong Key Laboratory of Information Security Technology Sun Yat-sen University 510006 China

Simon’s problem is an essential example demonstrating the faster speed of quantum computers than classical computers for solving some problems. The optimal separation between exact quantum and classical query complexities for Simon’s problem has been proved by Cai & Qiu. Generalized Simon’s problem can be described as follows. Given a function f : {0, 1}n → {0, 1}m, with the property that there is some unknown hidden subgroup S such that f(x) = f(y) iff x ⊕ y ∈ S, for any x, y ∈ {0, 1}n, where |S| = 2k for some 0 ≤ k ≤ n. The goal is to find S. For the case of k = 1, it is Simon’s problem. In this paper, we propose an exact quantum algorithm with O(n − k) queries and an non-adaptive deterministic classical algorithm with O(k√2n−k) queries for solving the generalized Simon’s problem. Also, we prove that their lower bounds are Ω(n − k) and Ω(√k2n−k), respectively. Therefore, we obtain a tight exact quantum query complexity Θ(n − k) and an almost tight non-adaptive classical deterministic query complexities Ω(√k2n−k) ∼ O(k√2n−k) for this problem. Copyright © 2019, The Authors. All rights reserved.

关键词： Quantum theory

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On s-uniform property of compressing sequences derived from primitive sequences modulo odd prime powers

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Science China(Information Sciences) 2017年第5期60卷 84-95页

作者： Yupeng JIANG Qun-Xiong ZHENG Dongdai LIN State Key Laboratory of Information Security Institute of Information EngineeringChinese Academy of Sciences State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Information Science and Technology Institute

Let Z/（p;） be the integer residue ring modulo pewith p an odd prime and e 2. We consider the suniform property of compressing sequences derived from primitive sequences over Z/（p;）. We give necessary and sufficient conditions for two compressing sequences to be s-uniform with α provided that the compressing map is of the form φ(x;, x;,..., x;) = g(x;) + η(x;, x;,..., x;), where g(x;) is a permutation polynomial over Z/（p） and η is an（e-1）-variable polynomial over Z/（p）.

关键词： compressing map linear recurring sequence primitive sequence permutation polynomial s uniform

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Overlapping Community Detection Based on Influence and Seeds Extension

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2019年第1期47卷 153-160页

作者： Yu, Zhi-Yong Chen, Ji-Jie Guo, Kun Chen, Yu-Zhong Xu, Qian College of Mathematics and Computer Sciences Fuzhou University FuzhouFujian350116 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing FuzhouFujian350116 China Ministry of Education Key Laboratory of Spatial Data Mining & Information Sharing FuzhouFujian350116 China State Grid Info-Telecom Great Power Science and Technology Co. Ltd. FuzhouFujian350003 China

Community detection is a significant research direction in the research of social networks. To improve the quality of seeds selection and expansion, we propose an influence seeds extension overlapping community detection (i-SEOCD) algorithm for overlapping community detection. First, i-SEOCD uses a node influence strategy to find the seed communities with tight structures. Second, on the basis of the seed communities, we calculate the similarity among communities and their neighbor nodes. The nodes whose similarity is greater than a predefined threshold are selected. Third, the strategy of optimizing a self-adaptive function is adopted to expand the communities. Finally, the free nodes in the network are assigned to their corresponding communities in order to find out all the overlapping community structures. Experiments on the real and artificial networks show that i-SEOCD is capable of discovering overlapping communities in complex social networks efficiently. © 2019, Chinese Institute of Electronics. All right reserved.

关键词： Population dynamics

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