International Journal of Artificial Intelligence Research
Vol 7, No 1 (2023): June 2023

Vulnerability Detection With K-Nearest Neighbor and Naïve Bayes Method using Machine Learning

Herman Herman (Department of Informatics, Universitas Ahmad Dahlan, Yogyakarta)
Imam Riadi (Department of Information System, Universitas Ahmad Dahlan, Yogyakarta)
Yudi Kurniawan (Department of Informatics, Universitas Ahmad Dahlan, Yogyakarta)



Article Info

Publish Date
30 Jun 2023

Abstract

In this day and age, the use of the Internet has increased. SQL injection is a serious security threat on the Internet for various dynamic websites. As the use of the Internet for various online services increases, so make the security threats that exist on the Web. SQL injection attacks are one of the most serious security vulnerabilities on the Web. Most of these vulnerabilities are caused by a lack of input validation and the use of SQL parameters. SQLMap is an application from the Kali Linux operating system that is useful for injecting data on a website by using the features available in this application. In this paper, author conducts a security assessment to detect attacks on a website, more precisely to detect SQL Injection attacks, using the K-Nearest Neighbor method and naïve bayes. The results obtained are that the website being tested has SQL Injection vulnerabilities, and the K-Nearest Neighbor method is the best method for this case because it has an accuracy of 94.2%. In comparison, the Naïve Bayes method has an accuracy of 80%.

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Journal Info

Abbrev

IJAIR

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

International Journal Of Artificial Intelligence Research (IJAIR) is a peer-reviewed open-access journal. The journal invites scientists and engineers throughout the world to exchange and disseminate theoretical and practice-oriented topics of Artificial intelligent Research which covers four (4) ...