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8th International Congress of Information and Communication Technology, ICICT 2018

作者： Yu, Changhe Lan, Julong Xie, JiChao Hu, Yuxiang National Digital Switching System Engineering and Technological R and D Center Zhengzhou450002 China

The QoS-aware traffic classification techniques of SdN networks is the basis for network to provide fine-grained QoS traffic engineering. In this paper, we propose an architecture which combines deep packet detection and semi-supervised machine learning of multi-classifier in SdN. This architecture can classify flows into different QoS categories. Based on this, network can achieve fine-grained adaptive QoS traffic engineering. Moreover, through deep packet detection techniques, network can maintain a dynamic flow database. Classifier can adapt to the rapid emergence of network application and fickle traffic characteristics of current network by periodically re-training with the dynamic flow database. Experiments verify that our classification framework can achieve good classification accuracy. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Network architecture

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An Intelligent Evaluation Model for decision Scheme Based on deep Learning

An Intelligent Evaluation Model for Decision Scheme Based on...

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第二届人工智能、网络与信息技术国际研讨会

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

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.

关键词： SAE An Intelligent Evaluation Model for decision Scheme Based on deep Learning Model

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Active perceptive dynamic scheduling mechanism based on negative feedback 8

Active perceptive dynamic scheduling mechanism based on nega...

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8th International Congress of Information and Communication Technology, ICICT 2018

作者： Lv, Yingying Guo, Yunfei Chen, Qiang Cheng, Guozhen Chen, Yang National Digital Switching System Engineering and Technological R and D Center Zhengzhou Henan450002 China

With the popularization of the Internet, the production and living of people and even the security development of the country have been more and more dependent on cyberspace, the importance of cyberspace has become increasingly prominent. Network security should be paid more and more attention to. Mimicry defense is one of active defense technologies. We focused on the dHr architecture and give a research on mimicry scheduling mechanism based on negative feedback and we have analyzed the feasibility of this method in theory. © 2018 The Authors. Published by Elsevier Ltd.

关键词： Network security

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A Combination of rNN and CNN for Attention-based relation Classification

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Procedia Computer Science 2018年 131卷 911-917页

作者： Xiaobin Zhang Fucai Chen ruiyang Huang National Digital Switching System Engineering & Techological R&D center ZhengZhou 450002 China

relation classification plays an important role in the field of natural language processing (NLP). Previous research on relation classification has verified the effectiveness of using convolutional neural network (CNN) and recurrent neural network (rNN). In this paper, we proposed a model that combine the rNN and CNN (rCNN), which will Give full play to their respective advantages: rNN can learn temporal and context features, especially long-term dependency between two entities, while CNN is capable of catching more potential features. We experiment our model on the SemEval-2010 Task 8 dataset 1 , and the result shows that our method is superior to most of the existing methods.

关键词： relation classification CNN rNN Word2Vec part-of-speech (POS) tags

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Overview of 5G security technology

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Science China(Information Sciences) 2018年第8期61卷 107-131页

作者： Xinsheng JI Kaizhi HUANG Liang JIN Hongbo TANG Caixia LIU Zhou ZHONG Wei YOU Xiaoming XU Hua ZHAO Jiangxing WU Ming YI National Digital Switching System Engineering & Technological R&D Center Zhengzhou 450002 China National Digital Switching System Engineering & Technological R&D Center

The 5 th-generation mobile communication system(5 G) has higher security requirements than previous systems. Accordingly, international standard organizations, operators, and equipment manufacturers are focusing extensively on 5 G security technology. This paper analyzes the security requirements of 5 G business applications, network architecture, the air interface, and user privacy. The development trends of5 G security architecture are summarized, with a focus on endogenous defense architecture, which represents a new trend in 5 G security development. Several incremental 5 G security technologies are reviewed, including physical layer security, lightweight encryption, network slice security, user privacy protection, and block chain technology applied to 5 G.

关键词： 5G security endogenous defense mimic defense physical layer security lightweight encryption network slice security user privacy preservation block chain

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research on C-E Fingerprint Extraction of Emitter

Research on C-E Fingerprint Extraction of Emitter

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IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Jiaying Yue Liuyang Gao Nae Zheng National Digital Switching System Engineering and Technological R&D Center (NDSC) Information Engineering University (IEU) Zhengzhou CO China

Aiming at the problem of limited presentation ability and easy drift of results for a single feature, a joint fingerprint feature extraction algorithm based on the complexity and entropy of instantaneous parameter (C-E) is proposed. From the perspective of signal information integrity, this paper multi-extract the secondary features of instantaneous amplitude, frequency and phase, and obtain the box dimension, information dimension, information entropy, as well as the Hilbert envelope spectrum information entropy newly proposed in this paper. Finally, the features are fused into C-E features to identify the individual radiation source. Compared with single class features, the recognition rate of the joint features is greatly improved at little time cost. In simulation experiment, the accuracy increases by 15.2% and 19.7% than fractal dimension and entropy respectively. And features have good independence and noise resistance under different environments.

关键词： Feature extraction Entropy Fingerprint recognition Complexity theory Fractals Time-domain analysis data mining

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Improving resiliency of Software-defined Networks with Network Coding-based Multipath routing

Improving Resiliency of Software-Defined Networks with Netwo...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Jianjian Ai Hongchang Chen Zehua Guo Guozhen Cheng Thar Baker National Digital Switching System Engineering & Technological R&D Center Beijing Institute of Technology Liverpool John Moores University

Traditional network routing protocol exhibits high statics and singleness, which provide significant advantages for the attacker. There are two kinds of attacks on the network: active attacks and passive attacks. Existing solutions for those attacks are based on replication or detection, which can deal with active attacks; but are helpless to passive attacks. In this paper, we adopt the theory of network coding to fragment the data in the Software-defined Networks and propose a network coding-based resilient multipath routing scheme. First, we present a new metric named expected eavesdropping ratio to measure the resilience in the presence of passive attacks. Then, we formulate the network coding-based resilient multipath routing problem as an integer-programming optimization problem by using expected eavesdropping ratio. Since the problem is NP-hard, we design a Simulated Annealing-based algorithm to efficiently solve the problem. The simulation results demonstrate that the proposed algorithms improve the defense performance against passive attacks by about 20% when compared with baseline algorithms.

关键词： Eavesdropping routing Encoding delays Computers resilience routing protocols

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Infinite Motif Stochastic Blockmodel for role discovery in Networks

Infinite Motif Stochastic Blockmodel for Role Discovery in N...

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International Conference on Advances in Social Network Analysis and Mining, ASONAM

作者： Yulong Pei Jianpeng Zhang George Fletcher Mykola Pechenizkiy Eindhoven University of Technology Eindhoven the Netherlands National Digital Switching System Engineering & Technological R&D Center Zhengzhou China

ISBN: (数字)9781450368681

ISBN: (纸本)9781450368681

role/block discovery is an essential task in network analytics so it has attracted significant attention recently. Previous studies on role discovery either relied on first or second-order structural information to group nodes but neglected the higherorder information or required the number of roles/blocks as the input which may be unknown in practice. To overcome these limitations, in this paper we propose a novel generative model, infinite motif stochastic blockmodel (IMM), for role discovery in networks. IMM takes advantage of high-order motifs in the generative process and it is a nonparametric Bayesian model which can automatically infer the number of roles. To validate the effectiveness of IMM, we conduct experiments on synthetic and real-world networks. The obtained results demonstrate IMM outperforms other blockmodels in role discovery task.

关键词： Stochastic processes Inference algorithms Bayes methods Social network services Task analysis Measurement Approximation algorithms

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A sensitivity analysis of attention-gated convolutional neural networks for sentence classification

arXiv

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arXiv 2019年

作者： Liu, Yang Zhang, Jianpeng Gao, Chao Qu, Jinghua Ji, Lixin National Digital Switching System Engineering and Technological R&D Center Zhengzhou450002 China Information Engineering University Zhengzhou450002 China

In this paper, we investigate the effect of different hyperparameters as well as different combinations of hyperparameters settings on the performance of the Attention-Gated Convolutional Neural Networks (AGCNNs), e.g., the kernel window size, the number of feature maps, the keep rate of the dropout layer, and the activation function. We draw practical advice from a wide range of empirical results. Through the sensitivity analysis, we further improve the hyperparameters settings of AGCNNs. Experiments show that our proposals could achieve an average of 0.81% and 0.67% improvements on AGCNN-NLreLU-rand and AGCNN-SELU-rand, respectively;and an average of 0.47% and 0.45% improvements on AGCNN-NLreLU-static and AGCNN-SELU-static, respectively. Copyright © 2019, The Authors. All rights reserved.

关键词： Sensitivity analysis

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Heterogeneous Executors Scheduling Algorithm for Mimic defense systems

Heterogeneous Executors Scheduling Algorithm for Mimic Defen...

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IEEE International Conference on Computer and Communication engineering Technology (CCET)

作者： Zhaoqi Wu Jin Wei National Digital Switching System Engineering & Technological R&D Center Zhengzhou China School of Computer Science Fudan University China

A key aspect of the mimetic defense system is the scheduling of heterogeneous executions to ensure that the system is dynamic. The existing scheduling strategy only performs random scheduling to satisfy heterogeneity and service quality. Combined with the historical information of the arbiter in the mimicry defense system, this paper proposed a random seed scheduling algorithm based on historical confidence for maximum heterogeneity and quality of service. First, the seed performer is randomly selected in the historical confidence executor that satisfies the threshold, and then the scheduling scheme is determined according to the maximum heterogeneity type and the quality of service indicator. The simulation results showed that the scheduling period of the algorithm is lower than the random scheduling algorithm. However, the scheduling effect is higher than the random scheduling algorithm, which achieved a good dynamic balance between dynamics, security, and quality of service.

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