汽车开放系统架构AUTOSAR (Automotive Open System Architecture)由于其软硬解耦、重用性强等特点,受到越来越多主机厂的青睐。而基于AUTOSAR架构的E2E (End To End)安全通信机制,和传统架构添加循环冗余校验以及信息序列号标识等机制...汽车开放系统架构AUTOSAR (Automotive Open System Architecture)由于其软硬解耦、重用性强等特点,受到越来越多主机厂的青睐。而基于AUTOSAR架构的E2E (End To End)安全通信机制,和传统架构添加循环冗余校验以及信息序列号标识等机制相比,E2E能够实现跨ECU平台的安全通行,兼容性和实用性较强。本文主要介绍车载通信故障类型、E2E保护和文件配置形式,同时进行整车环境的端对端保护通信机制的搭建,在实车环境中对E2E保护进行测试和验证,通过实践案例来促进对E2E深层次的应用。展开更多
为了支持GIG体系结构、设计和工程学中的应用,研究了可重复使用的GIG(Global Information Grid)仿真平台工具的开发。首先,利用传统的系统工程方法来设计GIG仿真平台,通过大量有用的性能分析完成相关GIG体系结构和设计。其次,在考虑自...为了支持GIG体系结构、设计和工程学中的应用,研究了可重复使用的GIG(Global Information Grid)仿真平台工具的开发。首先,利用传统的系统工程方法来设计GIG仿真平台,通过大量有用的性能分析完成相关GIG体系结构和设计。其次,在考虑自动化模拟构造的基础上设计了GIG仿真平台、开发了GIG拓扑模型。接着,讨论了GIG网络环境中最初研究BGP(Border Gateway Protocol)的性能,并且通过仿真实验进行验证平台的有效性。最后,提出了未来仿真平台研究的几点工作,以此来改进仿真平台在解决GIG体系结构、设计和工程学应用中的使用范围。展开更多
We investigate the design of satellite network slicing for the first time to provide customized services for the diversified applications,and propose a novel scheme for satellite end-to-end(E2E) network slicing based ...We investigate the design of satellite network slicing for the first time to provide customized services for the diversified applications,and propose a novel scheme for satellite end-to-end(E2E) network slicing based on 5G technology,which provides a view of common satellite network slicing and supports flexible network deployment between the satellite and the ground.Specifically,considering the limited satellite network resource and the characteristics of the satellite channel,we propose a novel satellite E2E network slicing architecture.Therein,the deployment of the network functions between the satellite and the ground is coordinately considered.Subsequently,the classification and the isolation technologies of satellite network sub-slices are proposed adaptively based on 5G technology to support resource allocation on demand.Then,we develop the management technologies for the satellite E2E network slicing including slicing key performance indicator(KPI) design,slicing deployment,and slicing management.Finally,the analysis of the challenges and future work shows the potential research in the future.展开更多
Deep learning(DL)is a subdivision of machine learning(ML)that employs numerous algorithms,each of which provides various explanations of the data it consumes;mobile ad-hoc networks(MANET)are growing in promi-nence.For...Deep learning(DL)is a subdivision of machine learning(ML)that employs numerous algorithms,each of which provides various explanations of the data it consumes;mobile ad-hoc networks(MANET)are growing in promi-nence.For reasons including node mobility,due to MANET’s potential to provide small-cost solutions for real-world contact challenges,decentralized management,and restricted bandwidth,MANETs are more vulnerable to security threats.When protecting MANETs from attack,encryption and authentication schemes have their limits.However,deep learning(DL)approaches in intrusion detection sys-tems(IDS)can adapt to the changing environment of MANETs and allow a sys-tem to make intrusion decisions while learning about its mobility in the environment.IDSs are a secondary defiance system for mobile ad-hoc networks vs.attacks since they monitor network traffic and report anything unusual.Recently,many scientists have employed deep neural networks(DNNs)to address intrusion detection concerns.This paper used MANET to recognize com-plex patterns by focusing on security standards through efficiency determination and identifying malicious nodes,and mitigating network attacks using the three algorithms presented Cascading Back Propagation Neural Network(CBPNN),Feedforward-Neural-Network(FNN),and Cascading-Back-Propagation-Neural-Network(CBPNN)(FFNN).In addition to Convolutional-Neural-Network(CNN),these primary forms of deep neural network(DNN)building designs are widely used to improve the performance of intrusion detection systems(IDS)and the use of IDS in conjunction with machine learning(ML).Further-more,machine learning(ML)techniques than their statistical and logical methods provide MANET network learning capabilities and encourage adaptation to differ-ent environments.Compared with another current model,The proposed model has better average receiving packet(ARP)and end-to-end(E2E)performance.The results have been obtained from CBP,FFNN and CNN 74%,82%and 85%,respectively,by the time(27,18,and 17 s).展开更多
随着汽车产业的发展趋于成熟,汽车的安全性备受关注,汽车开放式软件架构(automotive open system architecture,AUTOSAR)结合功能安全的要求对端到端(end to end,E2E)的通信作了规定。主要对AUTOSAR 4.2.2版本中E2E Profile Variant 1A...随着汽车产业的发展趋于成熟,汽车的安全性备受关注,汽车开放式软件架构(automotive open system architecture,AUTOSAR)结合功能安全的要求对端到端(end to end,E2E)的通信作了规定。主要对AUTOSAR 4.2.2版本中E2E Profile Variant 1A的保护机制进行了研究,使用Cubas和System desk工具在BSW和RTE层对E2E模块进行了配置,在应用层实现了对通信报文的E2E校验。最后使用CANoe对通信报文进行了仿真和验证,结果表明E2E通信保护机制可以有效地对通信报文中的失效类型进行检测并作相应的处理。展开更多
文摘汽车开放系统架构AUTOSAR (Automotive Open System Architecture)由于其软硬解耦、重用性强等特点,受到越来越多主机厂的青睐。而基于AUTOSAR架构的E2E (End To End)安全通信机制,和传统架构添加循环冗余校验以及信息序列号标识等机制相比,E2E能够实现跨ECU平台的安全通行,兼容性和实用性较强。本文主要介绍车载通信故障类型、E2E保护和文件配置形式,同时进行整车环境的端对端保护通信机制的搭建,在实车环境中对E2E保护进行测试和验证,通过实践案例来促进对E2E深层次的应用。
文摘为了支持GIG体系结构、设计和工程学中的应用,研究了可重复使用的GIG(Global Information Grid)仿真平台工具的开发。首先,利用传统的系统工程方法来设计GIG仿真平台,通过大量有用的性能分析完成相关GIG体系结构和设计。其次,在考虑自动化模拟构造的基础上设计了GIG仿真平台、开发了GIG拓扑模型。接着,讨论了GIG网络环境中最初研究BGP(Border Gateway Protocol)的性能,并且通过仿真实验进行验证平台的有效性。最后,提出了未来仿真平台研究的几点工作,以此来改进仿真平台在解决GIG体系结构、设计和工程学应用中的使用范围。
文摘We investigate the design of satellite network slicing for the first time to provide customized services for the diversified applications,and propose a novel scheme for satellite end-to-end(E2E) network slicing based on 5G technology,which provides a view of common satellite network slicing and supports flexible network deployment between the satellite and the ground.Specifically,considering the limited satellite network resource and the characteristics of the satellite channel,we propose a novel satellite E2E network slicing architecture.Therein,the deployment of the network functions between the satellite and the ground is coordinately considered.Subsequently,the classification and the isolation technologies of satellite network sub-slices are proposed adaptively based on 5G technology to support resource allocation on demand.Then,we develop the management technologies for the satellite E2E network slicing including slicing key performance indicator(KPI) design,slicing deployment,and slicing management.Finally,the analysis of the challenges and future work shows the potential research in the future.
文摘Deep learning(DL)is a subdivision of machine learning(ML)that employs numerous algorithms,each of which provides various explanations of the data it consumes;mobile ad-hoc networks(MANET)are growing in promi-nence.For reasons including node mobility,due to MANET’s potential to provide small-cost solutions for real-world contact challenges,decentralized management,and restricted bandwidth,MANETs are more vulnerable to security threats.When protecting MANETs from attack,encryption and authentication schemes have their limits.However,deep learning(DL)approaches in intrusion detection sys-tems(IDS)can adapt to the changing environment of MANETs and allow a sys-tem to make intrusion decisions while learning about its mobility in the environment.IDSs are a secondary defiance system for mobile ad-hoc networks vs.attacks since they monitor network traffic and report anything unusual.Recently,many scientists have employed deep neural networks(DNNs)to address intrusion detection concerns.This paper used MANET to recognize com-plex patterns by focusing on security standards through efficiency determination and identifying malicious nodes,and mitigating network attacks using the three algorithms presented Cascading Back Propagation Neural Network(CBPNN),Feedforward-Neural-Network(FNN),and Cascading-Back-Propagation-Neural-Network(CBPNN)(FFNN).In addition to Convolutional-Neural-Network(CNN),these primary forms of deep neural network(DNN)building designs are widely used to improve the performance of intrusion detection systems(IDS)and the use of IDS in conjunction with machine learning(ML).Further-more,machine learning(ML)techniques than their statistical and logical methods provide MANET network learning capabilities and encourage adaptation to differ-ent environments.Compared with another current model,The proposed model has better average receiving packet(ARP)and end-to-end(E2E)performance.The results have been obtained from CBP,FFNN and CNN 74%,82%and 85%,respectively,by the time(27,18,and 17 s).
文摘随着汽车产业的发展趋于成熟,汽车的安全性备受关注,汽车开放式软件架构(automotive open system architecture,AUTOSAR)结合功能安全的要求对端到端(end to end,E2E)的通信作了规定。主要对AUTOSAR 4.2.2版本中E2E Profile Variant 1A的保护机制进行了研究,使用Cubas和System desk工具在BSW和RTE层对E2E模块进行了配置,在应用层实现了对通信报文的E2E校验。最后使用CANoe对通信报文进行了仿真和验证,结果表明E2E通信保护机制可以有效地对通信报文中的失效类型进行检测并作相应的处理。
