网络数据传输高密度信息安全存储仿真

Simulation of Secure Storage of High Density Information for Network Data Transmission

对网络数据传输中高密度信息存储问题的研究,能够保证高密度信息的安全性。对高密度信息的安全存储,需要对数据存储过程中指纹梯度进行优化,实现高密度信息数据的流量分离,完成高密度信息的安全存储。传统方法对划分处理后的高密度信息进行统一编码,建立三维高密度信息存储模型,但忽略了高密度信息数据的流量分离,导致存储安全性偏低。提出基于压缩感知的网络数据传输中心高密度信息安全存储方法。对网络数据传输中心的高密度信息基于压缩感知进行测量,通过优化高密度信息存储节点测量矩阵和转发概率实现数据压缩重构,考虑高密度信息数据存储中使用强度,最小传输粒度等数字特征,对压缩重构数据存储过程中的指纹梯度进行优化,实现高密度信息数据的流量分离。实验结果表明,所提方法能够实现高密度信息高效存储,能够在流量分离的前提下降低信息安全存储时延。

This article proposes a secure storage method of high -density information in network data transmission center based on compressive sensing. Firstly, our method measures high density information of network data transmission center based on compressive sensing and realizes data compression reconstruction through optimization of measured matrix and forwarding probability of high density information storage node, then considers the digital characteristics such as the use of intensity in high density information data storage and the minimum transport granularity. Moreover, this method optimizes fingerprint gradient in process of data storage of compression reconstruction. Thus, we realize the traffic separation of high density information data. Simulation result shows that the proposed method can achieve the efficient storage of high density information and reduce the time delay of security storage of information under the premise of traffic separation.