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A secure anonymous authentication scheme for wireless communications using smart cards

International Journal of Network Security 2015年第3期17卷 237-245页

作者： Lu, Yanrong Wu, Xiaobo Yang, Xiaodong Information Security Center State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China National Engineering Laboratory for Disaster Backup and Recovery Beijing University of Posts and Telecommunications Beijing100876 China School of Software Engineering Yantai Vocational College Shandong Yantai264670 China College of Computer Science and Engineering Northwest Normal University Gansu Lanzhou730070 China

Wireless communications have become one of the most key parts in our everyday life, which give us facility on work and life but they still bring a great security risk. A crucial problem with wireless communications is to ensure the security of communication and prevent the privacy of communication entities revealing. Authentication is becoming an important issue when a mobile user (MU) wants to access services provided by the home agent (HA) in a visited foreign agent (FA). Recently, Kuo et al. proposed an authentication scheme and claimed that the proposed scheme was secure against different kinds of attacks. In this paper, we show that Kuo et al.'s scheme fails to resist insider and verifier attacks while it does not provide local verification. In addition, password change phase of Kuo et al.'s scheme also has a loophole. To remedy these shortcomings, an improved anonymous authentication scheme for wireless communications is proposed which is immune to various known types of attacks. Finally, in comparison with other existing schemes regarding security properties and performance, we show that our scheme has various kinds of security properties and is suitable for practical applications in wireless networks.

关键词： Authentication

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Let's work together: Fast tag identification by interference elimination for multiple RFID readers

Let's work together: Fast tag identification by interference...

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International Conference on Network Protocols

作者： Xuan Liu Bin Xiao Feng Zhu Shigeng Zhang College of Computer Science and Electronic Engineering Hunan University P. R. China Department of Computing The Hong Kong Polytechnic University Hong Kong State Key Laboratory for Novel Software Technology Nanjing University P.R. China School of Information Science and Engineering Central South University P. R. China

ISBN: (纸本)9781509032822

Fast tag identification is a fundamental challenging problem in multi-reader RFID systems. The challenge is how to effectively handle Reader-Tag (RT) collisions and Reader-Reader (RR) collisions among adjacent readers. These collisions are caused by interfering signals simultaneously transmitted by the readers, and may disallow adjacent readers to work together. Prior works tackle this problem by scheduling adjacent readers to work in different time slots. The readers that are selected to simultaneously work, however, are usually only a small proportion of the total readers. This greatly restricts the identification throughput. Our insightful investigation on the current tag identification protocol reveals that RT collisions are caused by asynchronous actions of readers. i.e., a reader transmits signal while its adjacent readers receive. We thus develop Slot Splitting, a technique that can completely eliminate RT collisions by synchronizing actions of readers. We also propose a reader selection algorithm that minimizes RR collisions by selecting a reader set with maximum reading efficiency. The combination of these new techniques inspires Federal, a Fast and efficient tag identification protocol with interference-elimination-based reader scheduling. To our knowledge, Federal is the first identification protocol that completely eliminates RT collisions and minimizes RR collisions in both regularly and randomly deployed multi-reader systems. We validate the feasibility of Slot Splitting with experiments on the USRP platform and evaluate the performance of Federal through extensive simulations. The results show that Federal can increase tag identification throughput by up to 218% compared with the state-of-the-art work.

关键词： Protocols Throughput Radiofrequency identification Interference Radiation detectors Conferences Monitoring

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10-elements linguistic truth-valued intuitionistic fuzzy first-order logic system

10-elements linguistic truth-valued intuitionistic fuzzy fir...

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International Conference of Young computer Scientists, Engineers and Educators, ICYCSEE 2015

作者： Wang, Yingxin Wen, Xin Zou, Li Marine Engineering College Dalian Maritime University China School of Computer and Information Technology Liaoning Normal University China State Key Laboratory for Novel Software Technology Nanjing University China

ISBN: (纸本)9783662462478

This paper presents 10-elements linguistic truth-valued intuitionistic fuzzy algebra and the properties based on the linguistic truth-valued implication algebra which is fit to express both comparable and incomparable information. This method can also deal with the uncertain problem which has both positive evidence and negative evidence at the same time.10-elements linguistic truthvalued intuitionistic fuzzy first-order logic system has been established in the intuitionistic fuzzy algebra. © Springer-Verlag Berlin Heidelberg 2015.

关键词： Linguistics

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Radiation constrained wireless charger placement

Radiation constrained wireless charger placement

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Haipeng Dai Yunhuai Liu Alex X. Liu Lingtao Kong Guihai Chen Tian He State Key Laboratory for Novel Software Technology Nanjing University Nanjing Jiangsu CHINA Third Research Institute of Ministry of Public Security Shanghai CHINA Shanghai key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University Shanghai China Computer Science and Engineering University of Minnesota Minneapolis MN USA Department of Automation Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781467399548

Wireless Power Transfer has become a commercially viable technology to charge devices because of the convenience of no power wiring and the reliability of continuous power supply. This paper concerns the fundamental issue of wireless charger placement with electromagnetic radiation (EMR) safety. Although there are a few wireless charging schemes consider EMR safety, none of them addresses the charger placement issue. In this paper, we propose PESA, a wireless charger Placement scheme that guarantees EMR SAfety for every location on the plane. First, we discretize the whole charging area and formulate the problem into the Multidimensional 0/1 Knapsack (MDK) problem. Second, we propose a fast approximation algorithm to the MDK problem. Third, we optimize our scheme to improve speed by double partitioning the area. We prove that the output of our algorithm is better than (1 - ϵ) of the optimal solution to PESA with a smaller EMR threshold (1 - ϵ/2)Rt and a larger EMR coverage radius (1 + ϵ/2)D. We conducted both simulations and field experiments to evaluate the performance of our scheme. Our experimental results show that in terms of charging utility, our algorithm outperforms the prior art by up to 45.7%.

关键词： Safety Wireless communication Wireless sensor networks Approximation algorithms Partitioning algorithms Inductive charging Aggregates

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A Community Evolution Model Based on Visibility Graph

A Community Evolution Model Based on Visibility Graph

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第三十四届中国控制会议

作者： WANG Hong SUN Yan-shen School of Information Science and Engineering Shandong Normal University Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Department of Earth Sciences Zhejiang University

ISBN: (纸本)9781467374439

One of the most important work to analyze networks is community detection. We present a dynamic community discovery method based on Visibility Graph. Firstly, we put forward related definitions of Visibility Graph for multi-dimensional time series. Then, we present algorithms to describe how to use Visibility Graph in finding communities in complex networks. Finally, we present algorithms to find dynamic multi-relational communities. We apply our method in some real data sets. Experimental results show that our methods do better for finding dynamic communities in complex networks.

关键词： community evolution,visibility graph,community discovery,complex network

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P systems-based fuzzy c-means clustering algorithm with local spatial information for image segmentation

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ICIC Express Letters 2016年第4期10卷 839-848页

作者： Tan, Jing Yang, Yanxiang Wang, Jun Chen, Ke Peng, Hong Li, Ming Sichuan Province Key Laboratory of Power Electronics Energy-Saving Technologies and Equipment School of Electrical Engineering and Electronic Information No. 999 Jinzhou Rd Jinniu District Chengdu China School of Applied Technology No. 999 Jinzhou Rd Jinniu District Chengdu China Center of Radio Administrator and Technology Development School of Computer and Software Engineering Xihua University No. 999 Jinzhou Rd Jinniu District Chengdu China

Fuzzy c-means (FCM) clustering algorithm and its variants have several disadvantages in image segmentation: (1) easy to fall into local minima;(2) sensitive to noise and outliers. To overcome the disadvantages, this paper proposes a novel P systems-based FCM clustering algorithm, P_FCM. The proposed algorithm uses a tissuelike P system as its computing framework, in which the differential evolution mechanism is considered as the evolution rules of objects. In order to enhance the robustness and insensitiveness to noise and outliers, a factor that integrates the local space position information and the gray level relationship is combined into the objective function of P_FCM. The proposed P_FCM is evaluated on the synthetic, real and Berkeley images. The comparison results demonstrate the availability and effectiveness in the segmentation of the noisy images. © 2016, ICIC International.

关键词： Image segmentation

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Hierarchical CNN for traffic sign recognition

Hierarchical CNN for traffic sign recognition

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IEEE Symposium on Intelligent Vehicle

作者： Xuehong Mao Samer Hijazi Raúl Casas Piyush Kaul Rishi Kumar Chris Rowen Faculty of Electrical and Computer Engineering United States Naval Academy Annapolis MD USA School of Electronic Engineering Xidian University Xi’an China School of Computer and Information Science Hubei Engineering University Xiaogan China Centre for Quantum Computation & Intelligent Systems and the Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway Street Ultimo NSW Australia Center for Optical Imagery Analysis and Learning (OPTIMAL) State Key Laboratory of Transient Optics and Photonics Xi’an Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xi’an Shaanxi China

ISBN: (纸本)9781509018222

The Convolutional Neural Network (CNN) is a breakthrough technique in object classification and pattern recognition. It has enabled computers to achieve performance superior to humans in specialized image recognition tasks. Prior art CNNs learn object features by stacking multiple convolutional/non-linear layers in sequence on top of a classifier. In this work, we propose a Hierarchical CNN (HCNN) which is inspired by a coarse-to-fine human learning methodology. For a given dataset, we introduce a CNN-oriented clustering algorithm to separate classes into K subsets, which are referred to as families. Then, the HCNN algorithm trains K+1 classification CNNs: one CNN for family classification and K dedicated CNNs corresponding to each family for member classification. We evaluate this HCNN approach on the German Traffic Sign Recognition Benchmark (GTSRB), and achieve 99.67% correct detection rate (CDR), which is superior to the best reported results (99.46%) achieved by a single network.

关键词： Clustering algorithms Training Classification algorithms Measurement Partitioning algorithms Standards Neural networks

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Joint modeling of user check-in behaviors for point-of-interest recommendation 15

Joint modeling of user check-in behaviors for point-of-inter...

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24th ACM International Conference on information and Knowledge Management, CIKM 2015

作者： Yin, Hongzhi Zhou, Xiaofang Shao, Yingxia Wang, Hao Sadiq, Shazia University of Queensland School of Information Technology and Electrical Engineering QLD4072 Australia School of Computer Science and Technology Soochow University China School of EECS Peking University China Science and Technology on Integrated Information System Laboratory State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781450337946

Point-of-Interest (POI) recommendation has become an important means to help people discover attractive and interesting locations, especially when users travel out of town. However, extreme sparsity of user-POI matrix creates a severe challenge. To cope with this challenge, a growing line of research has exploited the temporal effect, geographical-social influence, content effect and word-of-mouth effect. However, current research lacks an integrated analysis of the joint effect of the above factors to deal with the issue of data-sparsity, especially in the out-of-town recommendation scenario which has been ignored by most existing work. In light of the above, we propose a joint probabilistic generative model to mimic user check-in behaviors in a process of decision making, which strategically integrates the above factors to effectively overcome the data sparsity, especially for out-of-town users. To demonstrate the applicability and flexibility of our model, we investigate how it supports two recommendation scenarios in a unified way, i.e., home-town recommendation and out-of-town recommendation. We conduct extensive experiments to evaluate the performance of our model on two real large-scale datasets in terms of both recommendation effectiveness and efficiency, and the experimental results show its superiority over other competitors. © 2015 ACM.

关键词： Location based services

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Galactic transient sources with the Cherenkov Telescope Array Observatory

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Monthly Notices of the Royal Astronomical Society 2025年第1期540卷 205–238页

作者： Abe, K Abe, S Abhir, J Abhishek, A Acero, F Acharyya, A Adam, R Aguasca-Cabot, A Agudo, I Aguirre-Santaella, A Alfaro, J Alfaro, R Alvarez-Crespo, N Alves Batista, R Amans, J-P Amato, E Ambrosi, G Ambrosino, F Angüner, E O Antonelli, L A Aramo, C Arcaro, C Arnesen, T T H Asano, K Ascasibar, Y Aschersleben, J Ashkar, H Augusto Stuani, L Baack, D Backes, M Balazs, C Balbo, M Baquero Larriva, A Barbosa Martins, V Barres de Almeida, U Barrio, J A Barrios-Jiménez, L Batković, I Batzofin, R Baxter, J Becerra González, J Becker Tjus, J Belmont, R Benbow, W Bernete, J Bernlöhr, K Berti, A Bertucci, B Beshley, V Bhattacharjee, P Bhattacharyya, S Bigongiari, C Bissaldi, E Blanch, O Blazek, J Bocchino, F Boisson, C Bolmont, J Bonnoli, G Bonollo, A Bordas, P Bosnjak, Z Bottacini, E Böttcher, M Bradascio, F Bronzini, E Brown, A M Brunelli, G Bulgarelli, A Burelli, I Burger-Scheidlin, C Burmistrov, L Burton, M Buscemi, M Cailleux, J Campoy-Ordaz, A Cantlay, B K Capasso, G Caproni, A Capuzzo-Dolcetta, R Caraveo, P Caroff, S Carosi, A Carosi, R Carquin, E Carrasco, M-S Cascone, E Cassol, F Castaldini, L Castrejon, N Castro-Tirado, A J Cerasole, D Ceribella, G Cerruti, M Chadwick, P M Chaty, S Chen, A W Chernyakova, M Chiavassa, A Chudoba, J Chytka, L Cicciari, G M Cifuentes, A Coimbra Araujo, C H Colapietro, M Conforti, V Contreras, J L Cortina, J Costa, A Costantini, H Cotter, G Cristofari, P Cuevas, O Curtis-Ginsberg, Z D’Aì, A D’Amico, G D’Ammando, F Dai, S Dazzi, F de Bony de Lavergne, M De Caprio, V De Cesare, G De Frondat Laadim, F de Gouveia Dal Pino, E M De Lotto, B De Lucia, M de Martino, D de Menezes, R de Naurois, M de Ona Wilhelmi, E de Souza, V del Peral, L del Valle, M V Delgado, C Dell’aiera, M Della Valle, M della Volpe, D Depaoli, D Devin, J Di Girolamo, T Di Piano, A Di Pierro, F Di Tria, R Di Venere, L Diebold, S Dignam, C Dima, R Dinesh, A Djuvsland, J Dominik, R M Dominis Prester, D Donini, A Dorner, D Dörner, J Doro, M Dubos, C Ducci, L Dwarkadas, V V Ebr, J Eckner, C Egberts, K Einecke, S Elsässer, D Emery Department of Physics Tokai University 4-1-1 Kita-Kaname Hiratsuka Kanagawa 259-1292 Japan Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-ha Kashiwa Chiba 277-8582 Japan ETH Zürich Institute for Particle Physics and Astrophysics Otto-Stern-Weg 5 CH-8093 Zürich Switzerland INFN and Università degli Studi di Siena Dipartimento di Scienze Fisiche della Terra e dell’Ambiente (DSFTA) Sezione di Fisica Via Roma 56 I-53100 Siena Italy Université Paris-Saclay Université Paris Cité CEA CNRS AIM F-91191 Gif-sur-Yvette Cedex France FSLAC IRL 2009 CNRS/IAC E-38205 La Laguna Tenerife Spain University of Alabama Tuscaloosa Department of Physics and Astronomy Gallalee Hall Box 870324 Tuscaloosa AL 35487-0324 USA Université Côte d’Azur Observatoire de la Côte d’Azur CNRS Laboratoire Lagrange UF 06304 Nice France Laboratoire Leprince-Ringuet CNRS/IN2P3 École Polytechnique Institut Polytechnique de Paris F-91120 Palaiseau France Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Martí i Franquès 1 E-08028 Barcelona Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n E-18008 Granada Spain Institute for Computational Cosmology and Department of Physics Durham University South Road Durham DH1 3LE UK Pontificia Universidad Católica de Chile Av. Libertador Bernardo O’Higgins 340 8331150 Santiago Chile Universidad Nacional Autónoma de México Delegación Coyoacán 04510 Ciudad de México Mexico IPARCOS-UCM Instituto de Física de Partículas y del Cosmos and EMFTEL Department Universidad Complutense de Madrid E-28040 Madrid Spain Instituto de Física Teórica UAM/CSIC and Departamento de Física Teórica Universidad Autónoma de Madrid c/ Nicolás Cabrera 13-15 Campus de Cantoblanco UAM E-28049 Madrid Spain LUTH GEPI and LERMA Observatoire de Paris Université PSL Université Paris Cité CNRS 5 place Jules Janssen F-92190 Meudon France INAF – Osservatorio

A wide variety of Galactic sources show transient emission at soft and hard X-ray energies: low- and high-mass X-ray binaries containing compact objects, isolated neutron stars exhibiting extreme variability as magnetars as well as pulsar-wind nebulae. Although most of them can show emission up to MeV and/or GeV energies, many have not yet been detected in the TeV domain by Imaging Atmospheric Cherenkov Telescopes. In this paper, we explore the feasibility of detecting new Galactic transients with the Cherenkov Telescope Array Observatory (CTAO) and the prospects for studying them with Target of Opportunity observations. We show that CTAO will likely detect new sources in the TeV regime, such as the massive microquasars in the Cygnus region, low-mass X-ray binaries with low-viewing angle, flaring emission from the Crab pulsar-wind nebula or other novae explosions, among others. Since some of these sources could also exhibit emission at larger time-scales, we additionally test their detectability at longer exposures. We finally discuss the multiwavelength synergies with other instruments and large astronomical facilities.

关键词： binaries: general stars: magnetars novae cataclysmic variables pulsars: general gamma-rays: general

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An approach for service and tag recommendation based on mined domain knowledge

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Journal of Computational information systems 2015年第14期11卷 4965-4974页

作者： Li, Zheng Zhang, Lei Zhang, Neng School of Computer and Information Engineering Henan University Kaifeng China State Key Laboratory of Software Engineering School of Computer Wuhan University Wuhan China

Under the dynamically changing network environment, services from the composite services or mashup services may be unavailable or invalid. Moreover, as more and more services are published on the Internet, it is difficult for users to discover their desired services. Based on the domain knowledge generated from our previous service classification and clustering approaches, this paper proposes an approach for service and tag recommendation. Real services from ProgrammableWeb are used as data sets to demonstrate feasibility of the proposed approach. Experimental results show that our proposed approach can recommend functionally similar services for those deprecated services from mashup services, and can effectively recommend tags for a given service to facilitate service discovery. ©, 2015, Journal of Computational information systems. All right reserved.

关键词： Domain Knowledge

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