What is it about?
Researchers have proposed several methods to improve the security of applications by detecting source code vulnerabilities and malicious codes. This Systematic Literature Review (SLR) 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.
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Why is it important?
This paper aims to enable researchers to acquire in-depth knowledge in secure mobile application development while minimizing vulnerabilities by applying ML methods. Furthermore, researchers can use the discussions and findings of this SLR to identify potential future research and development directions.
Perspectives
This paper 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 while focusing more on ML-based methods.
Janaka Senanayake
Robert Gordon University
Read the Original
This page is a summary of: Android Source Code Vulnerability Detection: A Systematic Literature Review, ACM Computing Surveys, January 2023, ACM (Association for Computing Machinery),
DOI: 10.1145/3556974.
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