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IEEE Conference on Vehicular Technology (VTC)

作者： Yuanni Liu Man Xiao Yanyan Zhou di Zhang Jianhui Zhang Haris Gacanin Jianli Pan Chongqing University of Posts and Telecommunications Chongqing China Zhengzhou University Zhengzhou China National Digital Switching System Engineering & Technological R&D Center China Nokia Bell Labs Antwerp Belgium Department of Mathematics and Computer Science University of Missouri-St.Louis MO USA

ISBN: (数字)9781728152073

ISBN: (纸本)9781728140537

The information sharing among vehicles provides intelligent transport applications in the Internet of Vehicles (IoV), such as self-driving and traffic awareness. However, due to the openness of the wireless communication (e.g., dSrC), the integrity, confidentiality and availability of information resources are easy to be hacked by illegal access, which threatens the security of the related IoV applications. In this paper, we propose a novel risk Prediction-Based Access Control model, named rPBAC, which assigns the access rights to a node by predicting the risk level. Considering the impact of limited training datasets on prediction accuracy, we first introduce the Generative Adversarial Network (GAN) in our risk prediction module. The GAN increases the items of training sets to train the Neural Network, which is used to predict the risk level of vehicles. In addition, focusing on the problem of pattern collapse and gradient disappearance in the traditional GAN, we develop a combined GAN based on Wasserstein distance, named WCGAN, to improve the convergence time of the training model. The simulation results show that the WCGAN has a faster convergence speed than the traditional GAN, and the datasets generated by WCGAN have a higher similarity with real datasets. Moreover, the Neural Network (NN) trained with the datasets generated by WCGAN and real datasets (NN-WCGAN) performs a faster speed of training, a higher prediction accuracy and a lower false negative rate than the Neural Network trained with the datasets generated by GAN and real datasets (NN-GAN), and the Neural Network trained with the real datasets (NN). Additionally, the rPBAC model can improve the accuracy of access control to a great extent.

关键词： Gallium nitride Generative adversarial networks Generators Access control Training Predictive models Artificial neural networks

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Hardware acceleration resource allocation mechanism for VNF 8

Hardware acceleration resource allocation mechanism for VNF

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

作者： Fan, Hongwei Hu, Yuxiang Zhang, Shaojun ren, Quan National Digital Switching System Engineering and Technological R and D Center Kim Street No. 7 Zhengzhou450000 China

Improving the performance for VNF (Virtualized Network Function) by hardware acceleration is a hot research topic in SdN/NFV architecture. After introducing the acceleration resource for VNF, how to implement uniform deployment and allocation of the acceleration resources is an urgent problem to be solved. Thus in this paper, a unified deployment architecture of acceleration resource for VNF is proposed firstly. On the basis of architecture, the problem of acceleration resource allocation is modeled. By analyzing the influence of acceleration resource for VNF on deployment of service chains, we propose the evaluation index of acceleration resource allocation algorithm for VNF. Finally, we design a two-stage acceleration resource allocation algorithm to solve the problem. The experimental results show that the proposed algorithm can rationally allocate acceleration resources to nodes in the entire network and improve the efficiency of acceleration resource utilization. © 2018 The Authors. Published by Elsevier Ltd.

关键词： resource allocation

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An Aware-Scheduling Security Architecture with Priority-Equal Multi-Controller for SdN

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China Communications 2017年第9期14卷 144-154页

作者： Chao Qi Jiangxing Wu Guozhen Cheng Jianjian Ai Shuo Zhao National Digital Switching System Engineering & Technological R&D Center

Current SdN controllers suffer from a series of potential attacks. For example, malicious flow rules may lead to system disorder by introducing unexpected flow entries. In this paper, we propose Mcad-SA, an aware decision-making security architecture with multiple controllers, which could coordinate heterogeneous controllers internally as a "big" controller. This architecture includes an additional plane, the scheduling plane, which consists of transponder, sensor, decider and scheduler. Meanwhile it achieves the functions of communicating, supervising and scheduling between data and control plane. In this framework, we adopt the vote results from the majority of controllers to determine valid flow rules distributed to switches. Besides, an aware dynamic scheduling(AdS) mechanism is devised in scheduler to intensify security of Mcad-SA further. Combined with perception, AdS takes advantage of heterogeneity and redundancy of controllers to enable the control plane operate in a dynamic, reliable and unsteady state, which results in significant difficulty of probing systems and executing attacks. Simulation results demonstrate the proposed methods indicate better security resilience over traditional architectures as they have lower failure probability when facing attacks.

关键词： multi-controller security architec-ture aware scheduling

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Secret key generation based on private pilot under man-in-the-middle attack

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Science China(Information Sciences) 2017年第10期60卷 93-106页

作者： Yu HUANG Liang JIN Na LI Zhou ZHONG Xiaoming XU National Digital Switching System Engineering and Technological R&D Center National Engineering Laboratory for Mobile Network Technologies Beijing University of Posts and Telecommunications

Given the openness and invariance of public pilot, secret key generation(SKG) based on wireless channels is vulnerable to active attacks. In this paper, we explore man-in-the-middle(MITM) attacks, where the attacker acts as a transparent relay to intercept channel state information and deduce the generated *** prevent this type of attacks, a dynamic private pilot is generated, where legitimate nodes first consider the information authenticated between them as seed information for the private pilot, and then generate the private pilot based on this seed information according to the pilot requirements. Then, both the new seed information and secret keys are dynamicaally derived from wireless channels that are estimated with the private pilot instead of a public pilot. The proposed private pilot encrypts and authenticates wireless channels, allowing an SKG rate close to that without attackers. Analysis and simulation results show that the proposed SKG approach can effectively withstand an MITM attack.

关键词： private pilot man-in-the-middle attack secret key generation physical layer security

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Sequenced Switch migration for balancing controller loads in large-scale software-defined networking

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International Journal of Performability engineering 2018年第8期14卷 1848-1856页

作者： Yao, Lan Hu, Tao Lan, Julong National Digital Switching System Engineering R and D Center Zhengzhou450002 China

The proposal of the multi-controller has improved the scalability and reliability of software-defined networking (SdN), and the entire network is divided into several subdomains with the self-governed controller. due to the dynamic changes of network traffic in different subdomains, a new challenge has emerged for balancing loads on the distributed controllers. Switch migration, a promising method, is designed to solve the unbalanced distribution of controller loads. However, existing schemes implement switch migration without considering migration sequences and are characterized by long migration time and poor controller processing efficiency. To solve the above problems, this paper proposes the Sequenced Switch Migration (SSM) approach, which considers migration parameters (e.g., delay, traffic, residual capacity, and failure probability) for multi-objective optimization and achieves efficient switch migration using a sequenced manner. By executing the parallel and heuristic algorithms, SSM can reduce the execution time of migration while ensuring the performance requirements of controllers. The simulation results show that compared with the existing schemes, SSM reduces the total migration time by about 32.7% and decreases controller load variance by 28.5% when controllers are under high load condition. © 2018 Totem Publisher, Inc. All rights reserved.

关键词： Multiobjective optimization

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Pathological grading of Hepatocellular Carcinomas in MrI using a LASSO algorithm 1

Pathological grading of Hepatocellular Carcinomas in MRI usi...

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1st International Conference on Physics, Mathematics and Statistics, ICPMS 2018

作者： Gao, Fei Yan, Bin Chen, Jian Wu, Minghui Shi, dapeng National Digital Switching System Engineering and Technological R and D Center Henan Province ZhengZhou China Department of Radiology Henan General Hospital Henan Province ZhengZhou China

To investigate the predictive ability of radiomics signature for preoperative pathological grading of Hepatocellular Carcinomas (HCC), the no contrast MrI images were integrated and a comprehensive analysis was conducted to predict clinical outcomes using the radiomics features. Variable selection via LASSO and logistic regression were used to select the most-predictive radiomics features for the pathological grading. Cross-Validation with receiver operating characteristic (rOC) analysis was performed and the area under the rOC curve (AUC) was employed as the prediction metric. Overall, the prediction performances by radiomics features showed statistically significant correlations with pathological grading, however, improvement on the prediction performance by combining T1WI and T2WI data, classification performance obtained the AUC 0.829 in training dataset and the AUC 0.742 in validation dataset. This study consisted of 170 consecutive patients (training dataset: n=125;validation dataset, n=45). The results showed radiomics signature was developed and validated to be a significant predictor for discrimination HCC pathological grading, which may serve as a complementary tool for the preoperative tumour grading in HCC. © Published under licence by IOP Publishing Ltd.

关键词： Grading

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Orchestrating Network Functions in Software-defined Networks

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China Communications 2017年第2期14卷 104-117页

作者： Hongchao Hu Lin Pang Zhenpeng Wang Guozhen Cheng National Digital Switching System Engineering & Technological R&D Center Zhengzhou 450002 China

*** networking(SdN) enables *** companies to participate in the network function innovations. A number of instances for one network function will inevitably *** in the network. Although some orchestration architecture has been proposed to chain network functions, rare works are focused on how to optimize this process. In this paper, we propose an optimized model for network function orchestration, function combination model(FCM). Our main contributions are as following. First, network functions are featured with a new abstraction, and are open to external providers. And FCM identifies network functions using unique type, and organizes their instances distributed over the network with the appropriate way. Second, with the specialized demands, we can combine function instances under the global network views, and formulate it into the problem of Boolean linear program(BLP). A simulated annealing algorithm is designed to approach optimal solution for this BLP. Finally, the numerical experiment demonstrates that our model can create outstanding composite schemas efficiently.

关键词： software-defined network network function function orchestrating

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Toward a Scalable SdN Control Mechanism via Switch Migration

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China Communications 2017年第1期14卷 111-123页

作者： Guozhen Cheng Hongchang Chen Hongchao Hu Zhiming Wang National Digital Switching System Engineering & Technological R&D Center Zhengzhou 450002 China

dynamic Controller Provisioning Problem(dCPP) is a key problem for scalable SdN. Previously, the solution to this problem focused on adapting the number of controllers and their locations with changing network conditions, but ignored balancing control loads via switch migration. In this paper, we study a scalable control mechanism to decide which switch and where it should be migrated for more balanced control plane, and we define it as Switch Migration Problem(SMP). The main contributions of this paper are as follows. First, we define a SdN model to describe the relation between controllers and switches from the view of loads. Based on this model, we form SMP as a Network Utility Maximization(NUM) problem with the objective of serving more requests under available control resources. Second, we design a synthesizing distributed algorithm for SMP--- distributed Hopping Algorithm(dHA), by approximating our optimal objective via Log-Sum-Exp function. In dHA, individual controller performs algorithmic procedure independently. With the solution space F, we prove that the optimal gap caused by approximation is at most 1/βlog|F|, and dHA procedure is equal to implementation of a time-reversible Markov Chain process. Finally, the results are corroborated by several numerical simulations.

关键词： software-defined networking scalability switch migrations Markov chain

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Towards a dynamic Controller Scheduling-Timing Problem in Software-defined Networking

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China Communications 2017年第10期14卷 26-38页

作者： Zhenping Lu Fucai Chen Guozhen Cheng Chao Qi Jianjian Ai National Digital Switching System Engineering & Technological R&D Center Zhengzhou 450002 China

Controller vulnerabilities allow malicious actors to disrupt or hijack the Software-defined Networking. Traditionally, it is static mappings between the control plane and data plane. Adversaries have plenty of time to exploit the controller's vulnerabilities and launch attacks wisely. We tend to believe that dynamically altering such static mappings is a promising approach to alleviate this issue, since a moving target is difficult to be compromised even by skilled adversaries. It is critical to determine the right time to conduct scheduling and to balance the overhead afforded and the security levels guaranteed. Little previous work has been done to investigate the economical time in dynamic-scheduling controllers. In this paper, we take the first step to both theoretically and experimentally study the scheduling-timing problem in dynamic control plane. We model this problem as a renewal reward process and propose an optimal algorithm in deciding the right time to schedule with the objective of minimizing the long-term loss rate. In our experiments, simulations based on real network attack datasets are conducted and we demonstrate that our proposed algorithm outperforms given scheduling schemes.

关键词： software-defined networking network security controller

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QoS-aware Traffic Classification Architecture Using Machine Learning and deep Packet Inspection in SdNs

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Procedia Computer Science 2018年 131卷 1209-1216页

作者： Changhe Yu Julong Lan JiChao Xie Yuxiang Hu National Digital Switching System Engineering & Technological R&D Center Zhengzhou 450002 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.

关键词： traffic classification QoS machine learning SdN

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