车载自组网(VANET,vehicular ad hoc networks)具有无中心、移动性和多跳传输等特点,使得传统的密钥管理方式不再适用。可信计算技术的快速发展和成功应用为解决VANET的有效认证和信任评估问题提供了一条潜在途径。针对具有自组织特性的...车载自组网(VANET,vehicular ad hoc networks)具有无中心、移动性和多跳传输等特点,使得传统的密钥管理方式不再适用。可信计算技术的快速发展和成功应用为解决VANET的有效认证和信任评估问题提供了一条潜在途径。针对具有自组织特性的VANET网络,基于可信计算技术提出了一种新的认证和信任评估框架,引入了可信属性和可信等级的概念,给出了密钥管理结构和移动节点认证过程,着重指出了该框架潜在的实际应用。另外,阐述了在该框架下的信任评估方法。展开更多
First,we propose a cross-domain authentication architecture based on trust evaluation mechanism,including registration,certificate issuance,and cross-domain authentication processes.A direct trust evaluation mechanism...First,we propose a cross-domain authentication architecture based on trust evaluation mechanism,including registration,certificate issuance,and cross-domain authentication processes.A direct trust evaluation mechanism based on the time decay factor is proposed,taking into account the influence of historical interaction records.We weight the time attenuation factor to each historical interaction record for updating and got the new historical record data.We refer to the beta distribution to enhance the flexibility and adaptability of the direct trust assessment model to better capture time trends in the historical record.Then we propose an autoencoder-based trust clustering algorithm.We perform feature extraction based on autoencoders.Kullback leibler(KL)divergence is used to calculate the reconstruction error.When constructing a convolutional autoencoder,we introduce convolutional neural networks to improve training efficiency and introduce sparse constraints into the hidden layer of the autoencoder.The sparse penalty term in the loss function measures the difference through the KL divergence.Trust clustering is performed based on the density based spatial clustering of applications with noise(DBSCAN)clustering algorithm.During the clustering process,edge nodes have a variety of trustworthy attribute characteristics.We assign different attribute weights according to the relative importance of each attribute in the clustering process,and a larger weight means that the attribute occupies a greater weight in the calculation of distance.Finally,we introduced adaptive weights to calculate comprehensive trust evaluation.Simulation experiments prove that our trust evaluation mechanism has excellent reliability and accuracy.展开更多
针对大学校园里缺乏安全合法的兼职平台、兼职信息混杂的现状,采用Visual Studio2012作为开发工具,SQL Sever 2008进行数据库管理,开发出一个为用户提供特有会员安全认证机制、兼职双方信息评价机制、工资先付机制(即先领工资,再兼职,...针对大学校园里缺乏安全合法的兼职平台、兼职信息混杂的现状,采用Visual Studio2012作为开发工具,SQL Sever 2008进行数据库管理,开发出一个为用户提供特有会员安全认证机制、兼职双方信息评价机制、工资先付机制(即先领工资,再兼职,类似于淘宝支付体系)、兼职社区等功能的基于Web的兼职信息系统,有效解决现有的校园兼职平台的问题,保证良好的用户体验。展开更多
文摘车载自组网(VANET,vehicular ad hoc networks)具有无中心、移动性和多跳传输等特点,使得传统的密钥管理方式不再适用。可信计算技术的快速发展和成功应用为解决VANET的有效认证和信任评估问题提供了一条潜在途径。针对具有自组织特性的VANET网络,基于可信计算技术提出了一种新的认证和信任评估框架,引入了可信属性和可信等级的概念,给出了密钥管理结构和移动节点认证过程,着重指出了该框架潜在的实际应用。另外,阐述了在该框架下的信任评估方法。
基金This work is supported by the 2022 National Key Research and Development Plan“Security Protection Technology for Critical Information Infrastructure of Distribution Network”(2022YFB3105100).
文摘First,we propose a cross-domain authentication architecture based on trust evaluation mechanism,including registration,certificate issuance,and cross-domain authentication processes.A direct trust evaluation mechanism based on the time decay factor is proposed,taking into account the influence of historical interaction records.We weight the time attenuation factor to each historical interaction record for updating and got the new historical record data.We refer to the beta distribution to enhance the flexibility and adaptability of the direct trust assessment model to better capture time trends in the historical record.Then we propose an autoencoder-based trust clustering algorithm.We perform feature extraction based on autoencoders.Kullback leibler(KL)divergence is used to calculate the reconstruction error.When constructing a convolutional autoencoder,we introduce convolutional neural networks to improve training efficiency and introduce sparse constraints into the hidden layer of the autoencoder.The sparse penalty term in the loss function measures the difference through the KL divergence.Trust clustering is performed based on the density based spatial clustering of applications with noise(DBSCAN)clustering algorithm.During the clustering process,edge nodes have a variety of trustworthy attribute characteristics.We assign different attribute weights according to the relative importance of each attribute in the clustering process,and a larger weight means that the attribute occupies a greater weight in the calculation of distance.Finally,we introduced adaptive weights to calculate comprehensive trust evaluation.Simulation experiments prove that our trust evaluation mechanism has excellent reliability and accuracy.
文摘针对大学校园里缺乏安全合法的兼职平台、兼职信息混杂的现状,采用Visual Studio2012作为开发工具,SQL Sever 2008进行数据库管理,开发出一个为用户提供特有会员安全认证机制、兼职双方信息评价机制、工资先付机制(即先领工资,再兼职,类似于淘宝支付体系)、兼职社区等功能的基于Web的兼职信息系统,有效解决现有的校园兼职平台的问题,保证良好的用户体验。
