以轨道交通行业为背景,以智慧轨道交通(SRT)为对象,研究智慧轨道交通"全联网"(IoT)的基本组成框架和关键技术。将IoT置于下一代Internet背景之中,提出了以"智慧轨道交通骨干通信网"(SRT-BCN)为核心、以"基础...以轨道交通行业为背景,以智慧轨道交通(SRT)为对象,研究智慧轨道交通"全联网"(IoT)的基本组成框架和关键技术。将IoT置于下一代Internet背景之中,提出了以"智慧轨道交通骨干通信网"(SRT-BCN)为核心、以"基础接入网-资源网络"为轨道交通信息源和受主网络的"智慧轨道交通全联网(IoT for SRT,SRT-IoT)"的系统组成框架。针对轨道交通行业的特点,进一步将智慧轨道交通基础接入—资源网中与轨道交通有关部分划分为"列车接入—资源网"(TARN)和"地面接入—资源网"(GARN),并分析智慧轨道交通骨干通信网(SRT-BCN)和外围接入/资源网的特点,讨论相关的关键技术。重点讨论了与列车相关的TARN技术,得出需要进一步发展TARN相关网络技术的结论,为实现SRT-IoT更广泛的互联互通奠定研究基础。展开更多
从Internet发展历史及应用环境变化的角度讨论IoT(Internet of Things)提出背景、内涵、组成结构和体系结构等关键问题。在分析对IoT的典型定义的基础上,笔者认为"ITU把IoT作为Internet平台在应用领域实现人、机、和智能化物理对象...从Internet发展历史及应用环境变化的角度讨论IoT(Internet of Things)提出背景、内涵、组成结构和体系结构等关键问题。在分析对IoT的典型定义的基础上,笔者认为"ITU把IoT作为Internet平台在应用领域实现人、机、和智能化物理对象(SPO)信息全方位互通和实践普适计算理念的下一代Internet及其应用系统的概括"是对IoT更为合理的广义定义。以该定义为基础,全面地分析了"由多个用户域网(CPN)通过骨干通信子网互联"的基本组成结构,讨论了两类SPO-CPN的基本组成结构及其支撑技术;指出SPO的引入主要影响CPN资源网络中的接入部分,属于应用系统的范畴,对Internet基本技术影响甚微。笔者不赞同以欧盟为代表的把IoT定义为联物专用网的狭义定义,指出其IoT模型和体系结构研究混淆了网络平台与应用系统,实质上是网络应用系统模型和体系结构。展开更多
This paper presents a mechanism for detecting flooding-attacks. The simplicity of the mechanism lies in its statelessness and low computation overhead, which makes the detection mechanism itself immune to flooding-att...This paper presents a mechanism for detecting flooding-attacks. The simplicity of the mechanism lies in its statelessness and low computation overhead, which makes the detection mechanism itself immune to flooding-attacks. The SYN-flooding, as an instance of flooding-attack, is used to illustrate the anomaly detection mechanism. The mechanism applies an exponentially weighted moving average (EWMA) method to detect the abrupt net flow and applies a symmetry analysis method to detect the anomaly activity of the network flow. Experiment shows that the mechanism has high detection accuracy and low detection latency.展开更多
Since the frequency of network security incidents is nonlinear,traditional prediction methods such as ARMA,Gray systems are difficult to deal with the problem.When the size of sample is small,methods based on artifici...Since the frequency of network security incidents is nonlinear,traditional prediction methods such as ARMA,Gray systems are difficult to deal with the problem.When the size of sample is small,methods based on artificial neural network may not reach a high degree of preciseness.Least Squares Support Vector Machines (LSSVM) is a kind of machine learning methods based on the statistics learning theory,it can be applied to solve small sample and non-linear problems very well.This paper applied LSSVM to predict the occur frequency of network security incidents.To improve the accuracy,it used an improved genetic algorithm to optimize the parameters of LSSVM.Verified by real data sets,the improved genetic algorithm (IGA) converges faster than the simple genetic algorithm (SGA),and has a higher efficiency in the optimization procedure.Specially,the optimized LSSVM model worked very well on the prediction of frequency of network security incidents.展开更多
In order to solve the issue that existing direct anonymous attestation (DAA) scheme can not operate effectively in different domains,based on the original DAA scheme,a novel direct anonymous attestation protocol used ...In order to solve the issue that existing direct anonymous attestation (DAA) scheme can not operate effectively in different domains,based on the original DAA scheme,a novel direct anonymous attestation protocol used in multi domains environment is proposed and designed,in which,the certificate issuer located in outside of domain can be considered as a proxy server to issue the DAA certificate for valid member nodes directly.Our designed mechanism accords with present trusted computing group (TCG) international specification,and can solve the problems of practical authentication and privacy information protection between different trusted domains efficiently.Compared with present DAA scheme,in our protocol,the anonymity,unforgeability can be guaranteed,and the replay-attack also can be avoided.It has important referenced and practical application value in trusted computing field.展开更多
文摘以轨道交通行业为背景,以智慧轨道交通(SRT)为对象,研究智慧轨道交通"全联网"(IoT)的基本组成框架和关键技术。将IoT置于下一代Internet背景之中,提出了以"智慧轨道交通骨干通信网"(SRT-BCN)为核心、以"基础接入网-资源网络"为轨道交通信息源和受主网络的"智慧轨道交通全联网(IoT for SRT,SRT-IoT)"的系统组成框架。针对轨道交通行业的特点,进一步将智慧轨道交通基础接入—资源网中与轨道交通有关部分划分为"列车接入—资源网"(TARN)和"地面接入—资源网"(GARN),并分析智慧轨道交通骨干通信网(SRT-BCN)和外围接入/资源网的特点,讨论相关的关键技术。重点讨论了与列车相关的TARN技术,得出需要进一步发展TARN相关网络技术的结论,为实现SRT-IoT更广泛的互联互通奠定研究基础。
文摘从Internet发展历史及应用环境变化的角度讨论IoT(Internet of Things)提出背景、内涵、组成结构和体系结构等关键问题。在分析对IoT的典型定义的基础上,笔者认为"ITU把IoT作为Internet平台在应用领域实现人、机、和智能化物理对象(SPO)信息全方位互通和实践普适计算理念的下一代Internet及其应用系统的概括"是对IoT更为合理的广义定义。以该定义为基础,全面地分析了"由多个用户域网(CPN)通过骨干通信子网互联"的基本组成结构,讨论了两类SPO-CPN的基本组成结构及其支撑技术;指出SPO的引入主要影响CPN资源网络中的接入部分,属于应用系统的范畴,对Internet基本技术影响甚微。笔者不赞同以欧盟为代表的把IoT定义为联物专用网的狭义定义,指出其IoT模型和体系结构研究混淆了网络平台与应用系统,实质上是网络应用系统模型和体系结构。
基金TheNationalHighTechnologyResearchandDevelopmentProgramofChina(863Program) (No .2 0 0 2AA14 5 0 90 )
文摘This paper presents a mechanism for detecting flooding-attacks. The simplicity of the mechanism lies in its statelessness and low computation overhead, which makes the detection mechanism itself immune to flooding-attacks. The SYN-flooding, as an instance of flooding-attack, is used to illustrate the anomaly detection mechanism. The mechanism applies an exponentially weighted moving average (EWMA) method to detect the abrupt net flow and applies a symmetry analysis method to detect the anomaly activity of the network flow. Experiment shows that the mechanism has high detection accuracy and low detection latency.
基金supported in part by the National High Technology Research and Development Program of China ("863" Program) (No.2007AA010502)
文摘Since the frequency of network security incidents is nonlinear,traditional prediction methods such as ARMA,Gray systems are difficult to deal with the problem.When the size of sample is small,methods based on artificial neural network may not reach a high degree of preciseness.Least Squares Support Vector Machines (LSSVM) is a kind of machine learning methods based on the statistics learning theory,it can be applied to solve small sample and non-linear problems very well.This paper applied LSSVM to predict the occur frequency of network security incidents.To improve the accuracy,it used an improved genetic algorithm to optimize the parameters of LSSVM.Verified by real data sets,the improved genetic algorithm (IGA) converges faster than the simple genetic algorithm (SGA),and has a higher efficiency in the optimization procedure.Specially,the optimized LSSVM model worked very well on the prediction of frequency of network security incidents.
基金Acknowledgements This work was supported by Research Funds of Information Security Key Laboratory of Beijing Electronic Science ＆ Technology Institute National Natural Science Foundation of China（No. 61070219） Building Together Specific Project from Beijing Municipal Education Commission.
文摘In order to solve the issue that existing direct anonymous attestation (DAA) scheme can not operate effectively in different domains,based on the original DAA scheme,a novel direct anonymous attestation protocol used in multi domains environment is proposed and designed,in which,the certificate issuer located in outside of domain can be considered as a proxy server to issue the DAA certificate for valid member nodes directly.Our designed mechanism accords with present trusted computing group (TCG) international specification,and can solve the problems of practical authentication and privacy information protection between different trusted domains efficiently.Compared with present DAA scheme,in our protocol,the anonymity,unforgeability can be guaranteed,and the replay-attack also can be avoided.It has important referenced and practical application value in trusted computing field.
