A Study of Android Malware Detection Using Static Analysis

Smartphones have experienced blazing popularity and become more and more sophisticated over recent years; as a result, they have become an appealing target for malware authors. Malware keeps evolving and becomes more dangerous and harmful each day. Therefore, it is the need of the hour to detect and stop the spread of this previously unknown malware. It is also vital to detect and classify this malware, and machine learning has proven to be helpful in this field. For machine learning algorithms to achieve better performance, it is necessary to collect essential features from the application by reverse-engineering the APK file. However, this gives malware authors the upper hand as they started developing special anti-analysis techniques to mislead the machine learning-based analysis by obfuscation techniques to hide the application’s malicious behaviour. This study summarizes the static malware detection approach using different machine learning techniques, with emphasis on present-day research, challenges, and future directions.