Study on Software Vulnerability Characteristics and Its Identification Method
Chenlan Luo,
Wang Bo,
Huang Kun and
Lou Yuesheng
Mathematical Problems in Engineering, 2020, vol. 2020, 1-6
Abstract:
A method for identifying software data flow vulnerabilities is proposed based on the dendritic cell algorithm and the improved convolutional neural network to effectively solve the transmission errors in software data flow. In this method, we first gave the software data flow propagation model and constructed the data propagation tree structure. Secondly, we analyzed the running characteristics of the software, took the interaction among indexes into account, and identified data flow vulnerabilities using the dendritic cell algorithm and the improved convolutional neural network. Finally, we conducted an in-depth study on the performance of this method and other algorithms through mathematical simulation. The results show that this method has better advantages in detection time, storage cost, and software code size.
Date: 2020
References: Add references at CitEc
Citations:
Downloads: (external link)
http://downloads.hindawi.com/journals/MPE/2020/1583132.pdf (application/pdf)
http://downloads.hindawi.com/journals/MPE/2020/1583132.xml (text/xml)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:1583132
DOI: 10.1155/2020/1583132
Access Statistics for this article
More articles in Mathematical Problems in Engineering from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().