Classification of Phishing Attack Solutions by Employing Deep Learning Techniques: A Systematic Literature Review

Author:

Benavides Eduardo,Fuertes Walter,Sanchez Sandra,Sanchez Manuel

Publisher

Springer Singapore

Cited by 56 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. Cyber security in smart agriculture: Threat types, current status, and future trends;Computers and Electronics in Agriculture;2024-11

2. A Filter-Based Feature Selection for Robust Phishing Attack Detection using XGBoost;International Journal of Advanced Research in Science, Communication and Technology;2024-08-17

3. Phishing URLs Using Machine Learning Hybrid Stacking Classifier Approach with XGBoost, Random Forest and Extra Trees;2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS);2024-06-28

4. Enhancing Network Security: Leveraging Isolation Forest for Malware Detection;2024 2nd International Conference on Advancement in Computation & Computer Technologies (InCACCT);2024-05-02

5. Deep Reinforcement Learning-based Malicious URL Detection with Feature Selection;2024 IEEE 3rd International Conference on AI in Cybersecurity (ICAIC);2024-02-07

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