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Research Article

Academia Journal of Scientific Research Research  8(5): 186-192, May 2020
DOI: 10.15413/ajsr.2020.0401
ISSN: 2315-7712
2020 Academia Publishing 

Abstract


Risk assessment model of cross site script vulnerability based on detection

 

Accepted 6th March, 2020

Xiaolin Zhao, Yaoyuan Liang, Xinyu Hou, Jingfeng Xue, Mingzhe Pei and Hui Peng

Beijing Institute of Technology, Beijing 100081, China.


 
It has become necessary in recent years to study the security of different levels of interaction on network due to the increasing importance of network in all walks of life, in order to ensure the security of network applications and users. Cross site scripting vulnerabilities are common in web applications with frequent user interaction, which affect application security and user data security. In this study, the principle of cross site script vulnerability is evaluated, and the detection part of the model is designed based on the dynamic black box model. On the basis of the detection, the existing fuzzy comprehensive evaluation model is improved according to the dynamic detection results. The evaluation index system is established by selecting the evaluation index through AHP (Analytic hierarchy process), and the quantitative assessment model of cross-site scripting vulnerability risk for web applications is created. Through the experiment and comparison with the existing classical evaluation model and the evaluation results in related references, the effectiveness of the evaluation model is proved. The results show that the detection-based evaluation model designed in this study can measure the security of cross-site scripting vulnerabilities in Web applications.

Key words: Cross site script vulnerability, dynamic black box detection, fuzzy comprehensive evaluation, AHP.
 

This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Cite this article as:

Zhao X, Liang Y, Hou X, Xue X, Pei M, Peng H (2020). Risk assessment model of cross site script vulnerability based on detection Acad. J. Sci. Res. 8(5): 186-192.

 

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