Context-sensitive and keyword density-based supervised machine learning techniques for malicious webpage detection

Author:

Altay Betul,Dokeroglu TanselORCID,Cosar Ahmet

Publisher

Springer Science and Business Media LLC

Subject

Geometry and Topology,Theoretical Computer Science,Software

Cited by 24 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. A Holistic Review on Detection of Malicious Browser Extensions and Links using Deep Learning;2024 IEEE 3rd International Conference on AI in Cybersecurity (ICAIC);2024-02-07

2. Research on Machine Learning Method for Extracting Malicious Web Page Features;2023 IEEE 11th Joint International Information Technology and Artificial Intelligence Conference (ITAIC);2023-12-08

3. IDTracker: Discovering Illicit Website Communities via Third-party Service IDs;2023 53rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN);2023-06

4. Malicious website identification using design attribute learning;International Journal of Information Security;2023-03-24

5. MM-ConvBERT-LMS: Detecting Malicious Web Pages via Multi-Modal Learning and Pre-Trained Model;Applied Sciences;2023-03-06

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