Article Per Year (5 Year)
p-Index From 2019 - 2024
0.23
P-Index
This Author published in this journals
All Journal International Journal of Artificial Intelligence Research
Yudi Kurniawan
Department of Informatics, Universitas Ahmad Dahlan, Yogyakarta
Computer Science & IT Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Vulnerability Detection With K-Nearest Neighbor and Naïve Bayes Method using Machine Learning Herman Herman; Imam Riadi; Yudi Kurniawan
International Journal of Artificial Intelligence Research Vol 7, No 1 (2023): June 2023
Publisher : STMIK Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29099/ijair.v7i1.795

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%.
Co-Authors Herman Herman Imam Riadi