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A deep learning based misbehavior classification scheme for intrusion detection in cooperative intelligent transportation systems

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Digital Communications and Networks 2023年第5期9卷 1113-1122页

作者： Tejasvi Alladi Varun Kohli Vinay Chamola f.richard yu Department of Computer Science and Information Systems BITS-PilaniPilani Campus333031India Department of Electrical and Electronics Engineering&APPCAIR BITS-PilaniPilani Campus333031India Department of Systems and Computer Engineering Carleton UniversityOttawaONK1S 5B6Canada

With the rise of the Internet of Vehicles(IoV)and the number of connected vehicles increasing on the roads,Cooperative Intelligent Transportation Systems(C-ITSs)have become an important area of *** the number of Vehicle to Vehicle(V2V)and Vehicle to Interface(V2I)communication links increases,the amount of data received and processed in the network also *** addition,networking interfaces need to be made more secure for which existing cryptography-based security schemes may not be ***,there is a need to augment them with intelligent network intrusion detection *** machine learning-based intrusion detection and anomaly detection techniques for vehicular networks have been proposed in recent ***,given the expected large network size,there is a necessity for extensive data processing for use in such anomaly detection *** learning solutions are lucrative options as they remove the necessity for feature ***,with the amount of vehicular network traffic increasing at an unprecedented rate in the C-ITS scenario,the need for deep learning-based techniques is all the more *** work presents three deep learning-based misbehavior classification schemes for intrusion detection in IoV networks using Long Short Term Memory(LSTM)and Convolutional Neural Networks(CNNs).The proposed Deep Learning Classification Engines(DCLE)comprise of single or multi-step classification done by deep learning models that are deployed on the vehicular edge *** data received by the Road Side Units(RSUs)is pre-processed and forwarded to the edge server for classifications following the three classification schemes proposed in this *** proposed classifiers identify 18 different vehicular behavior types,the f1-scores ranging from 95.58%to 96.75%,much higher than the existing *** running the classifiers on testbeds emulating edge servers,the prediction performance and prediction time comparison of

关键词： Vehicular Ad-hoc Networks(VANETs) Intelligent Transportation Systems(ITS) Artificial Intelligence(AI) Deep Learning Internet of Things(IoT)

Vibration Control of an Experimental flexible Manipulator Against Input Saturation

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IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1340-1342页

作者： Zhijia Zhao Sentao Cai Ge Ma f.richard yu the School of Mechanical and Electrical Engineering Guangzhou UniversityGuangzhou 510006 the Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ) Shenzhen 518060China the Guangdong Laboratory of Artificial Intelligence and Digital Economy(SZ) College of Computer Science&Software EngineeringShenzhen UniversityShenzhen 518060China

Dear Editor, This letter considers the control problem of an experimental flexible manipulator in position tracking, vibration suppression, and saturation compensation. Based on the backstepping technology and a Nussbaum function, we develop an anti-windup control to restrain the manipulator’s vibration, realize the desire trajectory tracking, and eliminate the saturation.

关键词： restrain eliminate Vibration

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GUEST EDITORIAL

China Communications 2023年第3期 4-6页

作者： Shanzhi Chen f.richard yu Weisong Shi Changle Li China Information and Communication Technology Group Co. Ltd.(CICT) State Key Laboratory of Wireless Mobile Communications SMIC IEEE VTS Mobile World newsletter IEEE Canadian Academy of Engineering(CAE) 7. Engineering Institute of Canada(EIC) 8. IET Department of Computer and Information Sciences at the University of Delaware(UD) State Key Laboratory of Integrated Services Networks of Xidian University

With the development of new generation of information and communication technology, the Internet of Vehicles(Io V)/Vehicle-to-Everything(V2X), which realizes the connection between vehicle and X(i.e., vehicles, pedestrians, infrastructures, clouds, etc.), is playing an increasingly important role in improving traffic operation efficiency and driving safety as well as enhancing the intelligence level of social traffic services.

关键词：

Integrated Sensing,Computing and Communications Technologies in IoV and V2X

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China Communications 2023年第3期20卷 I0002-I0004页

作者： Shanzhi Chen frichard yu Weisong Shi Changle Li China Information and Communication Technology Group Co. Ltd.(CICT) State Key Laboratory of Wireless Mobile Communications SMIC IEEE VTS Mobile World newsletter IEEE Canadian Academy of Engineering(CAE) Engineering Institute of Canada(EIC) IET Department of Computer and Information Sciences at the University of Delaware(UD) State Key Laboratory of Integrated Services Networks of Xidian University

With the development of new generation of information and communication technology,the Internet of Vehicles(IoV)/Vehicle-to-Everything(V2X),which realizes the connection between vehicle and X(i.e.,vehicles,pedestrians,infrastructures,clouds,etc.),is playing an increasingly important role in improving traffic operation efficiency and driving safety as well as enhancing the intelligence level of social traffic services.

关键词： driving traffic operation

Special issue on future network:software-defined networking

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frontiers of Information Technology & Electronic Engineering 2016年第7期17卷 603-605页

作者： Tao HUANG f.richard yu yun-jie LIU Beijing University of Posts and Telecommunications China Carleton University Canada Chinese Academy of Engineering China

Computer networks have to support an everincreasing array of applications,ranging from cloud computing in datacenters to Internet access for *** order to meet the various demands,a large number of network devices runn... 详细信息

关键词：计算机网络软件定义用户访问数据中心网络设备互联网数组协议

Resource Allocation and Power Control Policy for Device-to-Device Communication Using Multi-Agent Reinforcement Learning

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Computers, Materials & Continua 2020年第6期63卷 1515-1532页

作者： Yifei Wei Yinxiang Qu Min Zhao Lianping Zhang f.richard yu Beijing Key Laboratory of Work Safety Intelligent Monitoring Beijing University of Posts and TelecommunicationsBeijing100876China Alibaba Cloud Computing Hangzhou311121China Department of Systems and Computer Engineering Carleton UniversityOttawaK1S 5B6Canada

Device-to-Device(D2D)communication is a promising technology that can reduce the burden on cellular networks while increasing network *** this paper,we focus on the channel resource allocation and power control to improve the system resource utilization and network ***,we treat each D2D pair as an independent *** agent makes decisions based on the local channel states information observed by *** multi-agent Reinforcement Learning(RL)algorithm is proposed for our multi-user *** assume that the D2D pair do not possess any information on the availability and quality of the resource block to be selected,so the problem is modeled as a stochastic non-cooperative ***,each agent becomes a player and they make decisions together to achieve global ***,the multi-agent Q-learning algorithm based on game theory is ***,in order to accelerate the convergence rate of multi-agent Q-learning,we consider a power allocation strategy based on fuzzy C-means(fCM)*** strategy firstly groups the D2D users by fCM,and treats each group as an agent,and then performs multi-agent Q-learning algorithm to determine the power for each group of D2D *** simulation results show that the Q-learning algorithm based on multi-agent can improve the throughput of the *** particular,fCM can greatly speed up the convergence of the multi-agent Q-learning algorithm while improving system throughput.

关键词： D2D communication resource allocation power control multi-agent Q-learning fuzzy C-means

fUTURE INTERNET ARCHITECTURE AND TESTBEDS

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China Communications 2017年第10期14卷 I0001-I0002页

作者： Tao Huang f.richard yu Gaogang Xie yunjie Liu Beijing University of Posts and Telecommunications (BUPT) Carleton University Network Technology Research Center at Institute of Computing Technology Chinese Academy of Sciences the Science and Technology Committee of China Unicom

With the tremendous advances in the field of information and communications technology(ICT),and the emergence of new applications,such as 4K/8K,AR/VR,Internet of Things,and Industrial Internet and so on,the traditional Internet has faced severe challenges on scalability,flexibility,controllability,mobility and security and so *** order to cope with these challeng-

关键词：互联网测试平台工业网络架构通信技术可扩展性体系结构 ICT

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区块链网络拓扑优化和转发策略设计

通信学报 2022年第12期43卷 89-100页

作者：霍如程祥凤孙闯汪硕黄韬 frichard yu 北京工业大学信息学部北京100124 网络通信与安全紫金山实验室江苏南京211111 清华大学自动化系北京100084 北京邮电大学网络与交换技术国家重点实验室北京100876 加拿大卡尔顿大学信息技术学院渥太华KIS 5B6

为解决区块链网络的数据传输效率低问题,提出了区块链传输效率优化方法来优化网络拓扑和转发策略。首先,设计了可信值函数计算区块链节点的可信值,综合考虑可信值和传输时间构建树形拓扑。然后,基于树形拓扑设计转发路径选择策略,以最... 详细信息

为解决区块链网络的数据传输效率低问题,提出了区块链传输效率优化方法来优化网络拓扑和转发策略。首先,设计了可信值函数计算区块链节点的可信值,综合考虑可信值和传输时间构建树形拓扑。然后,基于树形拓扑设计转发路径选择策略,以最小整体并发传输时间为目标,建立节点关于其邻居节点转发次序的转发表。为了减小节点变化对树形拓扑的影响,提出了拓扑动态优化策略局部调整树形拓扑。转发路径选择策略使整个数据传输过程具有最小传输时间,动态优化策略避免重构全网拓扑,有效缩短数据传输时间。仿真结果表明,与权重优先算法相比,所提方法的传输时间减小了约20%,显著提高了数据传输效率。

关键词：区块链网络树形拓扑转发路径选择拓扑动态优化传输效率

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端到端时延上限确定的服务链部署算法

通信学报 2021年第11期42卷 66-78页

作者：王泽南张娇汪硕黄韬 f.richard yu 网络通信与安全紫金山实验室江苏南京211111 北京邮电大学网络与交换技术国家重点实验室北京100876 加拿大卡尔顿大学渥太华K1S 5B6

针对现有服务链部署算法无法保证通过服务链的每一个数据包的端到端时延问题,提出端到端时延上限确定的服务链部署算法。首先,基于网络演算得到服务链的端到端时延上限;然后,通过协同优化服务链路由与虚拟网络功能节点资源分配,实现确... 详细信息

针对现有服务链部署算法无法保证通过服务链的每一个数据包的端到端时延问题,提出端到端时延上限确定的服务链部署算法。首先,基于网络演算得到服务链的端到端时延上限;然后,通过协同优化服务链路由与虚拟网络功能节点资源分配,实现确定的服务链端到端时延上限。实验结果表明,所提算法能在提高服务链接收数量的同时,保证通过服务链的每一个数据包的端到端时延均满足业务需求。

关键词：端到端时延服务链网络功能虚拟化网络演算