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85th IEEE Vehicular Technology Conference, VTC Spring 2017

作者： Zhang, Bo Huang, Kaizhi Yi, Ming Yi, Mingliang National Digital Switching System Engineering and Technological R and D Center Zhengzhou450002 China

ISBN: (纸本)9781509059324

For preventing the leakage of confidential messages sent to a marcocell user in dense heterogeneous networks, a physical layer security scheme based on base station cooperation is proposed in the paper. To improve transmission rate of confidential messages and make the downlink signals of other legitimate users interfere with eavesdroppers, the beamforming vectors at a macrocell base station and femtocell base stations are jointly optimized. The problem of maximizing the secrecy rate is modeled under the limitations of quality of service(QoS) and base station power. due to the intractability, this problem is recast into a convex Semidefinite Program(SdP) problem using the Semidefinite relaxation(Sdr) technique and the successive convex approximation(SCA) algorithm. Simulation results validate the efficacy and the security of the scheme. © 2017 IEEE.

关键词： Heterogeneous networks

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Secure Cryptography Infrastructures in the Cloud

Secure Cryptography Infrastructures in the Cloud

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IEEE Global Communications Conference

作者： dawei Chu Kaijie Zhu Quanwei Cai Jingqiang Lin Fengjun Li Le Guan Lingchen Zhang State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences School of Cyber Security University of Chinese Academy of Sciences National Digital Switching System Engineering & Technological R&D Center CHINA Data Assurance and Communication Security Research Center Chinese Academy of Sciences Department of Electrical Engineering and Computer Science The University of Kansas USA Department of Computer Science University of Georgia USA

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Information systems are deployed in clouds as virtual machines (VMs) for better agility, elasticity and reliability. It is necessary to safekeep their cryptographic keys, e.g., the private keys used in TLS and SSH, against various attacks. However, existing virtualization solutions do not improve the cryptography facilities of in-cloud systems. This paper presents SECrIN, a secure cryptography infrastructure for VMs in the cloud. SECrIN is composed of a) virtual cryptographic devices implemented in VM monitors (VMMs), and b) a device management tool integrated in the virtualization management system. A virtual device receives requests from VMs, computes with cryptographic keys within the VMM and returns results. The keys appear only in the VMM's memory space, so that they are kept secret even if the VMs were compromised. With the management tool, the operator of virtualization management systems assigns virtual cryptographic devices to a VM as well as other resources, while the tenant (or owner) of a VM still holds proper controls on the keys. The virtual devices work compatibly with live migration, and the cryptographic computations are not interrupted when the VMs are moving from a host to another. We develop the SECrIN prototype with KVM-QEMU and oVirt. Experimental results show that, it works compatibly with existing virtualization solutions, provides reliable cryptographic computing services for applications, and is secure against attacks happening in VMs.

关键词： Cryptography Virtualization Cloud computing Virtual machine monitors Password reliability Tools

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A forwarding graph embedding algorithm exploiting regional topology information

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Frontiers of Information Technology & Electronic engineering 2017年第11期18卷 1854-1866页

作者： Hong-chao HU Fan ZHANG Yu-xing MAO Zhen-peng WANG National Digital Switching System Engineering & Technological R&D Center Zhengzhou 450002 China

Network function virtualization （NFV） is a newly proposed technique designed to construct and manage network fimctions dynamically and efficiently. Allocating physical resources to the virtual network function forwarding graph is a critical issue in NFV. We formulate the forwarding graph embedding （FGE） problem as a binary integer programming problem, which aims to increase the revenue and decrease the cost to a service provider （SP） while considering limited network resources and the requirements of virtual functions. We then design a novel regional resource clustering metric to quantify the embedding potential of each substrate node and propose a topology-aware FGE algorithm called ＇regional resource clustering FGE＇（rrC-FGE）. After implementing our algorithms in C＋＋, simulation results showed that the total revenue was increased by more than 50 units and the acceptance ratio by more than 15%, and the cost of the service provider was decreased by more than 60 units.

关键词： Network function virtualization Virtual network function Forwarding graph embedding

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Change detection in Semantic Level for SAr Images

Change Detection in Semantic Level for SAR Images

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International Conference on Image, Vision and Computing (ICIVC)

作者： Tianqi Mao Wei Liu Yongjun Zhao Jie Huang China National Digital System Engineering and Technological R&D Center Zhengzhou China

ISBN: (纸本)9781538649923

Considering that the traditional change detection algorithms only focus on extracting the change area but ignore the change content identification, a novel change detection framework for synthetic aperture radar (SAr) images is proposed. The framework integrates the merits of unsupervised and supervised learning to detect changes in semantic level. First, the residual convolutional auto-encoder (rCAE) is designed to convert SAr image slices to the histogram representation. Then, we calculate the difference vectors and extract the change area by their norms. Finally, we classify the difference vectors of change region and identify the content of change. Experimental results indicate that the proposed method achieves significantly performance improvement over existing algorithms.

关键词： Synthetic aperture radar Semantics Training Feature extraction Convolution Histograms Marine vehicles

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Identification of conductive leakage signal in power cable based on Multi-Classification PSO-SVM 5

Identification of conductive leakage signal in power cable b...

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The 5th International Symposium on Electromagnetic Compatibility

作者： Zhisheng Qian Changlin Zhou Junping Cheng Qinmin Wang China national digital switch system engineering & technological R & D center

ISBN: (纸本)9781509051861;9781509051854

In order to effectively identify and extract the red signal from the leakage signal in the computer's power line,a method based on particle swarm optimization(PSO) is proposed to optimize the multi classification support vector machine(SVM).Firstly,the conductive leakage signal is *** the SVM penalty parameter and kernel parameter are optimized by PSO,the conduction leakage signal is trained and ***,the classification performance of the un-optimized SVM is compared with *** result shows that this method has higher classification rate than the grid search *** classification and recognition rate reaches 87.23%.

关键词： conductive leakage power cable PSO SVM

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A dHr-Based Security-Critical Task Scheduling Algorithm for Heterogeneous Processing system

A DHR-Based Security-Critical Task Scheduling Algorithm for ...

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IEEE International Conference on Computer and Communications

作者： Ye Shengzhao Zhao Bo Wei Shuai Yin Congyue Wang Sunan SoC Lab China National Digital Switching System Engineering & Technological R&D Center Zhengzhou China College of Communication & Engineering Shenzhen Polytechnic Schools Shenzhen China

ISBN: (纸本)9781538683408

Mimic defense techniques can solve unknown vulnerabilities as well as backdoors without prior knowledge based on dHr structure. Compared with traditional defense methods, dHr structure brings dynamic and heterogeneous factors into systems to enhance security. In this paper, we discuss the security-critical scheduling problem in dHr-based processing system and propose MHF algorithm according to the characters of heterogeneous processing nodes with different performance. While ensuring task schedulability, MHF algorithm improves the average heterogeneity of processing nodes as high as possible when allocating redundant versions of a task. Simulation results show that the average heterogeneity of MHF algorithm is 22.7% higher than that of rF algorithm when tasks' guarantee ratio approaches 100%.

关键词： Task analysis Security real-time systems redundancy Software Scheduling algorithms

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An Intelligent Evaluation Model for decision Scheme Based on deep Learning

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Journal of Physics: Conference Series 2019年第3期1176卷

作者： Wei Ou Zhaohui Yi Lan Cheng Ying Liao The Border and Coastal Defense College Urumqi China China National Digital Switching System Engineering & Technological R&D Center Zhengzhou China

Studying and constructing the intelligent decision-making model for simulation entity can effectively improve the credibility and immersion of wargaming, in which intelligent evaluation of decision scheme is the key module. To lower the reasoning complexity and shorten the decision time, an intelligent evaluation model based on Stacked Auto-Encoder (SAE) is proposed, which simulates the reasoning mode of human decision-making, and learns commander's knowledge and experience through unsupervised and supervised training. Then, to improve the robustness and generalization ability of the deep learning model, a de-noising training method and sparsity constraints are introduced. Finally, simulation experiment is carried out to verify the scientificity and effectiveness of the proposed model.

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Characteristic Analysis and Modeling for the Near Field radiation of FPGA 5

Characteristic Analysis and Modeling for the Near Field Radi...

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The 5th International Symposium on Electromagnetic Compatibility

作者： Junping Cheng Changlin Zhou daojie Yu Zhisheng Qian Mengjuan Chai China national digital switch system engineering & technological R&D center

ISBN: (纸本)9781509051861;9781509051854

To predict the radiation emission of the FPGA,the radiation emission model for the chip is proposed with ICEM and the simulation result is also presented in this *** linear near-field surface scan system(LNFS) following electromagnetic compatibility standard is applied to measure the *** is illustrated that the simulation results agree with the measurements,so the value of the model for practical application is verified.

关键词： electromagnetic compatibility(EMC) radiation emission(rC) LNFS FPGA

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Space Object Attitude and Position determination Based on Astrometry and Photometric data Fusion

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Procedia Computer Science 2018年 131卷 327-335页

作者： Jidong Qin Huafeng Peng Tongxin dang National Digital Switching System Engineering & Technology R & D Center No. 61 Science Road Zhengzhou Henan 450001 China National Key Laboratory of Science and Technology on Blind Signal No. 31 Dashi South Road Chengdu Sichuan 610041 China

The astronomical observation model, light curve model and solar radiation pressure force model are established to allow estimation of the positions and attitudes of space objects using a fusion of photometric and astronomical data. Existing algorithms for this purpose involve large errors. The proposed method firstly estimates the attitude of the object by using photometric and astronomical data fusion. Secondly, the position of the object is filtered by the estimated attitude. Theory and numerical simulations show the efficiency of the proposed method.

关键词： Attitude estimation Position estimation Light curve Geosynchronous satellite radio system of orbit determination

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rNN deep reinforcement Learning for routing Optimization

RNN Deep Reinforcement Learning for Routing Optimization

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International Conference on Computer and Communications (ICCC)

作者： Penghao Sun Junfei Li Julong Lan Yuxiang Hu Xin Lu China National Digital Switching System Engineering & Technological R&D Center (NDSC) Zhengzhou China China Electronics Technology Group Corporation 32th Research Institute Shanghai China

ISBN: (纸本)9781538683408

routing optimization has been discussed in network design for a long time. In recent years, new methods of routing strategy based on reinforcement Learning are being considered. In this paper, we propose a reinforcement learning based smart agent that can optimize routing strategy without human experience. Our proposed scheme is based on the collection of the traffic intensity in switches and the usage of a recurrent Neural Network based deep reinforcement learning model to train the agent. Simulation result shows that the proposed scheme can adjust the routing strategy dynamically according to the network condition and outperforms the traditional shortest path routing after trained.

关键词： routing reinforcement learning Neural networks Telecommunication traffic Training delays Optimization

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