University Links: Home Page | Site Map
Covenant University Repository

A Fuzzy Classifier-Based Penetration Testing for Web Applications

Alhassan, J. K. and Misra, Sanjay and Umar, A. and Maskeliunas, R. and Damasevicius, Robertas and Adewumi, A. O. (2018) A Fuzzy Classifier-Based Penetration Testing for Web Applications. In: Advances in Intelligent Systems and Computing. Springer, pp. 95-104.

[img] PDF
Download (1MB)


The biggest challenge of Web application is the inestimable losses arising from security flaws. Two approaches were advanced by a number of scholars to provide security to Web space. One of such approach is vulnerability assessment, which is a conscious effort to isolate, identify and recognize potentials vulnerabilities exploited by attackers. The second being the estimation and determination of level of risks/threats posed to Web applications by vul- nerabilities obvious to the developer (or tester); this is generally referred to as penetration testing. Recently, there is Vulnerability Assessment and Penetration Testing (VAPT) that combined these two schemes to improve safety and effec- tively combat the menace of attackers on Web applications. This paper proposed Fuzzy Classifier-based Vulnerability and Assessment Testing (FCVAPT) model to provide security for sensitive data/information in Web applications. Cross Site Scripting (XSS) and Structured Query Language (SQL) injections were selected for evaluation of proposed FCVAPT model. FCVAPT model’s classification performance for MSE, MAPE and RMSE were 33.33, 14.81% and 5.77% respectively. FCVAPT is considerably effective for detecting vulnerability and ascertaining the nature of threats/risks available to Web applications.

Item Type: Book Section
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science
Depositing User: Mr Adewole Adewumi
Date Deposited: 07 May 2018 17:18
Last Modified: 07 May 2018 17:18

Actions (login required)

View Item View Item