Machine learning algorithms for URLs classification
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Tarih
2022
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Phishing is a technique used to collect sensitive data from a user (password or credit card information) for future misuse by posing as a trustworthy source. It often takes advantage of the user's gullibility in ways that the user will not detect at first look, and in the worst-case scenario, the attacker maintains the user's data without the user's awareness. Typically, the URL is the first and simplest piece of information we know about a website. As a result, it is logical to design algorithms for distinguishing harmful from benign URLs. Additionally, accessing and downloading the website's material may be time-consuming and involves the danger of downloading potentially hazardous information. Machine Learning techniques are used to train a model on a collection of URLs specified as a set of characteristics and then predict and categorize the URLs as benign or dangerous. This technology enables us to identify and avoid possibly dangerous URLs shortly.
Açıklama
Anahtar Kelimeler
Feature Extraction, KNN, Logistic Regression, Naïve Bayes, SVM
Kaynak
Proceedings - 2022 International Conference on Artificial Intelligence of Things, ICAIoT 2022
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
Sayı
Künye
Al Zirjawi, S. S. K., Kashkool, H. J. M., Ibrahim, A. A., & Al, M. I. A. (2022). Machine learning algorithms for URLs classification. In 2022 International Conference on Artificial Intelligence of Things (ICAIoT). IEEE.
