Exploring Machine Learning Approaches for Detecting Android Malware: A Survey

Exploring Machine Learning Approaches for Detecting Android Malware: A Survey

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Authors- Hiral Patel, Associate Professor Dr.Mukta Agrawal

Abstract-The number of malicious applications targeting the Android platform has significantly expanded with the rise in usage of mobile devices. Malware is now exceedingly difficult to detect because of how carefully it is coded. The daily increase in the volume of malware has rendered manual procedures ineffective for detecting it. Traditional signature-based detection techniques, which rely on recognized malware patterns, frequently fall short of the task of identifying newly developed malware variants. The ever-evolving landscape of Android malware can be combated using machine learning techniques, which are more dynamic and flexible. This study provides a thorough analysis of machine learning-based methods for Android malware detection.

DOI: /10.61463/ijset.vol.12.issue6.360