Using Attribute-based Feature Selection Approaches and Machine Learning Algorithms for Detecting Fraudulent Website URLs

Author:

Aydin Mustafa,Butun IsmailORCID,Bicakci Kemal,Baykal Nazife

Publisher

IEEE

Cited by 14 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Graph Convolutional Networks for Malicious URLs Detection;2024 IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC);2024-05-24

2. An Efficient Hybrid Feature Selection Technique Toward Prediction of Suspicious URLs in IoT Environment;IEEE Access;2024

3. Facilitating Secure Web Browsing by Utilizing Supervised Filtration of Malicious URLs;IoT Based Control Networks and Intelligent Systems;2023-11-28

4. Classification and Identification of Phishing Websites based on Machine Learning;2023 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC);2023-11-02

5. Analysing the Accuracy of Detecting Phishing Websites using Ensemble Methods in Machine Learning;2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS);2023-02-02

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