Malicious XSS Code Detection with Decision Tree

Ömer KASIM

doi:https://doi.org/10.2339/politeknik.470332

Makale detayları

Malicious XSS Code Detection with Decision Tree

Yazarlar:

Ömer KASIM

Yayıncı:

Gazi University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Journal of Polytechnic 2020 Vol.23 Issue 1, pp.67-72

Belge Tipi:

Makale

Yayın Tarihi:

2/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000589810

Sıklık:

Aylık

eISSN:

2147-9429

DOI:

https://doi.org/10.2339/politeknik.470332

Özet:

 

Dynamic applications such as e-commerce, blogs, forums, e-governance, e-banking and portals that are in these platforms have become a part of our lives. However, a tremendous increase in the use of dynamic web and mobile applications has resulted in security vulnerabilities originating from the Hypertext Markup Language (HTML) coding system. Site-to-site Script Execution (XSS) attack is the largest contributors to security exploits. There are different models according to the dynamic content that XSS attacks use. The interest of the study is composed of attacks on visual content with the "img" tag. In study, an algorithm has been developed to detect XSS attacks with the decision tree which is motivated by the fact that they tend to be easier to implement and interpret than other quantitative data-driven methods. The algorithm that successfully classifies 392 of 400 malicious and clean codes in the data set with 8 different features. This result contributes to the use of secure internet without XSS attacks that use visual content..

 


Dynamic applications such as e-commerce, blogs, forums, e-governance, e-banking and portals that are in these platforms have become a part of our lives. However, a tremendous increase in the use of dynamic web and mobile applications has resulted in security vulnerabilities originating from the Hypertext Markup Language (HTML) coding system. Site-to-site Script Execution (XSS) attack is the largest contributors to security exploits. There are different models according to the dynamic content that XSS attacks use. The interest of the study is composed of attacks on visual content with the "img" tag. In study, an algorithm has been developed to detect XSS attacks with the decision tree which is motivated by the fact that they tend to be easier to implement and interpret than other quantitative data-driven methods. The algorithm that successfully classifies 392 of 400 malicious and clean codes in the data set with 8 different features. This result contributes to the use of secure internet without XSS attacks that use visual content..

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Makale detayları

Malicious XSS Code Detection with Decision Tree

Yazarlar: Ömer KASIM

Yayıncı: Gazi University

Ana Başlıklar: Uygulamalı fizik

Dergi: Journal of Polytechnic 2020 Vol.23 Issue 1, pp.67-72

Belge Tipi: Makale

Yayın Tarihi: 2/2020

Belge Dili: İngilizce

Document ID (Org No.): 2000589810

Sıklık: Aylık

eISSN: 2147-9429

DOI: https://doi.org/10.2339/politeknik.470332

Sayı

Yazarlar:

Ömer KASIM

Yayıncı:

Gazi University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Journal of Polytechnic 2020 Vol.23 Issue 1, pp.67-72

Belge Tipi:

Makale

Yayın Tarihi:

2/2020

Belge Dili:

İngilizce

Document ID (Org No.):

2000589810

Sıklık:

Aylık

eISSN:

2147-9429

DOI:

https://doi.org/10.2339/politeknik.470332