The Use of Machine Learning Techniques to Advance the Detection and Classification of Unknown Malware

Author:

Shhadat Ihab,Bataineh Bara’,Hayajneh Amena,Al-Sharif Ziad A.

Publisher

Elsevier BV

Subject

General Engineering

Cited by 36 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. SQL injection attack: Detection, prioritization & prevention;Journal of Information Security and Applications;2024-09

2. Android malware detection and identification frameworks by leveraging the machine and deep learning techniques: A comprehensive review;Telematics and Informatics Reports;2024-06

3. An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey;2024 IEEE International Conference on Electro Information Technology (eIT);2024-05-30

4. Android malware detection based on multi-feature fusion and deep learning;Fourth International Conference on Sensors and Information Technology (ICSI 2024);2024-05-06

5. Improving Windows Malware Detection Using the Random Forest Algorithm and Multi-View Analysis;International Journal of Software Engineering and Knowledge Engineering;2024-04-13

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