The Systematic Literature Review focuses on Android application analysis and source code vulnerability detection methods and tools by critically evaluating 118 carefully selected technical studies published between 2016 and 2022. It highlights the advantages, disadvantages, applicability of the proposed techniques, and potential improvements of those studies. Both Machine Learning (ML)-based methods and conventional methods related to vulnerability detection are discussed whilefocusing more on ML-based methods, since many recent studies conducted experiments with ML. Therefore, this article aims to enable researchers to acquire in-depth knowledge in secure mobile application development while minimizing the vulnerabilities by applying ML methods. Furthermore, researchers can use the discussions and findings of this SLR to identify potential future research and development directions.

Janaka Senanayake, Harsha Kalutarage, Mhd Omar Al-Kadri, Andrei Petrovski, Luca Piras

ACM Computing Surveys

Abstract:- https://dl.acm.org/doi/10.1145/3556974