可信计算下多播网络编码匿名通信仿真  被引量:1

Simulation of Multicast Network Coding Anonymous Communication under Trusted Computing

在线阅读下载全文

作  者:蔡威 冯光辉 CAI Wei;FENG Guang-hui(Department of Information Engineering,Institute of Zhengzhou Industrial Application Technology,Zhengzhou Henan 451150,China;School of Computer Science and Cyber Engineering,Guangzhou University,Guangdong Guangzhou 510006,China)

机构地区:[1]郑州工业应用技术学院信息工程学院,河南郑州451150 [2]广州大学计算机科学与网络工程学院,广东广州510006

出  处:《计算机仿真》2023年第10期408-411,472,共5页Computer Simulation

摘  要:由于通信数据中普遍存在随机非平稳噪声,影响通信安全,为了保障数据在通信过程中的安全性和完整性,提出基于可信计算的多播网络编码匿名通信方法。构建可信平台验证节点和用户身份的可信度,对存在随机非平稳噪声的通信数据进行稀疏变换,消除数据中存在的噪声。通过线性网络编码方法编码处理去噪后的通信数据,通过可信度量方法构建发送者和目标节点之间的网络编码匿名通信链路路径,完成通信数据的传输。采用签名加密方法验证数据的完整性和发送方身份的真实性,实现多播网络编码匿名通信。实验结果表明,所提方法的数据发送成功率高、平均传输时延低、平均丢包率低。Random non-stationary noise is common in communication data,affecting the communication security.In order to ensure the security and integrity of data during communication process,this paper proposed a method of multicast network coding anonymous communication based on trusted computing.Firstly,we built a trusted platform to verify the credibility of node and user ID,and sparsely transformed the communication data with random non-stationary noise,and thus to eliminate the noise from data.Secondly,we coded the denoised data using the linear network coding method,and then used the trust measurement method to construct a network coding anonymous communication link between sender and target nodes,thus completing the transmission of communication data.Finally,we verified the integrity of data and the authenticity of sender ID with the method of signature encryption.Thus,we realized the anonymous communication of multicast network coding.Experimental results show that the proposed method has high success rate of data transmission,low average transmission delay and low average packet loss rate.

关 键 词:可信计算 匿名通信 可信度量 网络编码 通信链路 

分 类 号:TP309[自动化与计算机技术—计算机系统结构]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象