Machine learning approaches for malware classification in android platform: a review

• Main Authors: Howida Alkaaf, Farkhana Muchtar, Salmah Fattah, Asraf Osman Ibrahim Elsayed, Carolyn Salimun, Hadzariah Ismail, Farhan Masud
• Format: Article
• Language: English; English
• Published: Semarak Ilmu Publishing 2025
• Subjects: LB1050.9-1091 Educational psychology; QA71-90 Instruments and machines
• Online Access: https://eprints.ums.edu.my/id/eprint/41927/1/ABSTRACT.pdf; https://eprints.ums.edu.my/id/eprint/41927/2/FULL%20TEXT.pdf; https://eprints.ums.edu.my/id/eprint/41927/; https://doi.org/10.37934/araset.48.1.248268

The rapid growth of Android applications has led to a continuous influx of Android malware. Numerous research has been undertaken to tackle that issue. Existing research has indicated that leveraging machine learning is a highly effective and promising approach for Android malware detection. This pa...