Artificial Intelligence and Dynamic Analysis-Based Web Application Vulnerability Scanner
Yazarlar (2)
Dr. Öğr. Üyesi Mehmet Ali YALÇINKAYA Kırşehir Ahi Evran Üniversitesi, Türkiye
Prof. Dr. Ecir Uğur Küçüksille Süleyman Demirel Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (ESCI dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Isecure | ||
| Dergi ISSN | 2008-2045 Wos Dergi Scopus Dergi | ||
| Dergi Tarandığı Indeksler | ESCI | ||
| Makale Dili | İngilizce | Basım Tarihi | 01-2024 |
| Cilt / Sayı / Sayfa | 16 / 1 / 55–77 | DOI | 10.22042/isecure.2023.367746.847 |
| Makale Linki | https://www.isecure-journal.com/article_183555_f52954f44ac33e6b456862c7a8ad3ad5.pdf | ||
| UAK Araştırma Alanları |
Bilgi Güvenliği ve Kriptoloji
Yapay Zeka
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| Özet |
| The widespread use of web applications and running on sensitive data has made them one of the most significant targets of cyber attackers. One of the most crucial security measures that can be taken is detecting and closing vulnerabilities on web applications before attackers. This study developed a web application vulnerability scanner based on dynamic analysis and artificial intelligence, which could test web applications using GET and POST methods and had test classes for 21 different vulnerability types. The developed vulnerability scanner was tested on a web application test laboratory, created within this study's scope and had 262 different web applications. A data set was created from the tests performed using the developed vulnerability scanner. In this study, web page classification was made using the mentioned data set as a first stage. The highest success rate in the page classification process was … |
| Anahtar Kelimeler |
| Data Mining | Machine Learning | Web Application Penetration Tests | Web Application Vulnerabilities |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| Scopus | 1 |
| Google Scholar | 8 |