An Android Malware Detection Approach Based on Static Feature Analysis Using Machine Learning Algorithms-Reference-Cited by-同舟云学术

An Android Malware Detection Approach Based on Static Feature Analysis Using Machine Learning Algorithms

Published:2022 Issue: Volume:201 Page:653-658
ISSN:1877-0509
Container-title:Procedia Computer Science
language:en
Short-container-title:Procedia Computer Science

Author:

Shatnawi Ahmed S.,Yassen Qussai,Yateem Abdulrahman

Publisher

Elsevier BV

Subject

General Engineering

Reference16 articles.

1. Alfalqi, K., Alghamdi, R., Waqdan, M., 2015. Android platform malware analysis. International Journal of Advanced Computer Science and Applications (IJACSA).

2. Escanilla, N.S., Hellerstein, L., Kleiman, R., Kuang, Z., Shull, J., Page, D., 2018. Recursive feature elimination by sensitivity testing, in: 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA), IEEE. pp. 40–47.

3. Goldsmith, A., 2005. Wireless communications. Cambridge university press.

4. Hahn, S., Protsenko, M., Müller, T., 2016. Comparative evaluation of machine learning-based malware detection on android. Sicherheit 2016-Sicherheit, Schutz und Zuverlässigkeit.

5. Johnson, S., Twilley, N., Zhang, T., Zhou, Z., Wu, S., 2014. Mobile computing: A look at concepts, problems and solutions.

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