分布式网络连续数据流脆弱点识别方法研究

万红霞

摘  要： 分布式网络连续数据流脆弱点识别能够有效地保证网络计算应用的安全性。为了提高识别效果，提出基于连续数据流脆弱点的错误信息识别方法，选取信号级错误及网络模块集传播的连续数据脆弱点特征，定义错误渗透率，分析当前模块脆弱数据流的传播错误，生成传播树定义分布式网路线脆弱信号影响因子，建立错误传递矩阵，并将不同数据错误对当前网络影响程度作为评判标准建立评价机制，根据权重从比特级、模块级、信号级识别连续数据流脆弱点。实验结果表明，所提的识别方法在分布式网络连续数据流脆弱点识别过程中具有較好的识别效果。

关键词： 脆弱点识别; 数据流脆弱点; 特征选取; 数据流分析; 影响因子构建; 评价机制

中图分类号： TN915.08?34                       文献标识码： A                         文章编号： 1004?373X（2020）13?0081?04

Research on vulnerable point recognition method for continuous data

flow in distributed network

WAN Hongxia1， 2

（1. Department of Computer Science & Technology， Jianghan Petroleum Institute， Jingzhou 434000， China;

2. Sinopec Geophysical Research Institute， Nanjing 211100， China）

Abstract： The identification of vulnerable points of continuous data flow in a distributed network can effectively guarantee the security of network computing applications. In order to improve the recognition effect， an error information recognition method based on vulnerable points of continuous data flow is proposed. Signal level errors and continuous data vulnerable point characteristics of network module set propagation are selected， the error penetration rate is defined， the propagation errors of the current module vulnerable data flow is analyzed to generate a propagation tree to define the distributed network route vulnerability signal impact factor and establish the error transfer matrix. The influence degree of different data errors on the current network is taken as the evaluation standard to establish an evaluation mechanism， and the vulnerable points of continuous data flow are identified from bit level， module level and signal level according to the weight. The experimental results show that the proposed identification method has a good identification effect in the process of identifying the vulnerable points of continuous data flow in distributed networks.

Keywords： vulnerability recognition; vulnerable point of data flow; feature selection; data flow analysis; influence factor construction; evaluation mechanism

0  引  言

在一些高科技行业领域，计算数据和计算系统的应用越来越广泛，例如：交通控制、医疗、发电、通信系统、航空航天系统等[1]。在这些领域中，计算系统的效率和可靠性至关重要，一旦出现计算问题，很有可能造成大面积的损失，甚至造成人员伤亡。分布式网络下，计算机通常需要进行高密度、高强度的应用计算[2?3]，数据流的连续性显得至关重要。在数据输出过程中，数据流在软件或者传输节点的影响下，会出现连续数据流脆弱点，这种脆弱点从广义上可以定义为数据系统中一些不好的特征成分或者数据部分。数据流脆弱点在外部入侵下可能会对当前计算机系统相关资源产生不利影响[4]。……