Multicriteria Decision and Machine Learning Algorithms for Component Security Evaluation: Library-Based Overview

被引:12
|
作者
Zhang, Jibin [1 ]
Nazir, Shah [2 ]
Huang, Ansheng [1 ]
Alharbi, Abdullah [3 ]
机构
[1] Petro China Southwest Oil & Gasfield Co, Mat Corp, Chengdu 610017, Peoples R China
[2] Univ Swabi, Dept Comp Sci, Swabi, Pakistan
[3] Taif Univ, Coll Comp & Informat Technol, Dept Informat Technol, At Taif 21944, Saudi Arabia
关键词
INTERNET;
D O I
10.1155/2020/8886877
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Components are the significant part of a system which plays an important role in the functionality of the system. Components are the reusable part of a system which are already tested, debugged, and experienced based on the previous practices. A new system is developed based on the reusable components, as reusability of components is recommended to save time, effort, and resources as such components are already made. Security of components is a significant constituent of the system to maintain the existence of the component as well as the system to function smoothly. Component security can protect a component from illegal access and changing its contents. Considering the developments in information security, protecting the components becomes a fundamental issue. In order to tackle such issues, a comprehensive study report is needed which can help practitioners to protect their system. The current study is an endeavor to report some of the existing studies regarding component security evaluation based on multicriteria decision and machine learning algorithms in the popular searching libraries.
引用
收藏
页数:14
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