JANAKA SENANAYAKE j.senanayake@rgu.ac.uk
Research Student
JANAKA SENANAYAKE j.senanayake@rgu.ac.uk
Research Student
Dr Harsha Kalutarage h.kalutarage@rgu.ac.uk
Lecturer
Mhd Omar Al-Kadri
Andrei Petrovski
Luca Piras
Mobile application developers sometimes might not be serious about source code security and publish apps to the marketplaces. Therefore, it is essential to have a fully automated security solutions generator to integrate security-by-design into the development practices, especially for the Android platform. This research proposes a Machine Learning (ML) based highly accurate method to detect Android source code vulnerabilities. A new labelled dataset containing Android source code vulnerability samples was generated initially. The dataset was used to train binary and multi-class classification based ML models, to identify code issues by following a static analysis approach. The proposed model can detect code vulnerabilities with a 0.90 F1-Score and vulnerability categories (CWE) with a 0.96 F1-Score. By integrating this with the Android development environment, app developers can analyse source code and identify security vulnerabilities in real-time. The proposed framework can be extended to suggest suitable patches to overcome the source code issues by providing real-time fixes in future.
SENANAYAKE, J., KALUTARAGE, H., AL-KADRI, M.O., PETROVSKI, A. and PIRAS, L. 2022. Developing secured android applications by mitigating code vulnerabilities with machine learning. In ASIA CCS '22: proceedings of the 17th ACM (Association for Computing Machinery) Asia conference on computer and communications security 2022 (ASIA CCS 2022), 30 May - 3 June 2022, Nagasaki, Japan. New York: ACM [online], pages 1255-1257. Available from: https://doi.org/10.1145/3488932.3527290
Conference Name | 17th Asia Conference on computer and communications security 2022 (ASIA CCS 2022) |
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Conference Location | Nagasaki, Japan |
Start Date | May 30, 2022 |
End Date | Jun 2, 2022 |
Acceptance Date | Feb 7, 2022 |
Online Publication Date | May 30, 2022 |
Publication Date | May 30, 2022 |
Deposit Date | Jul 29, 2022 |
Publicly Available Date | Jul 29, 2022 |
Publisher | ACM Association for Computing Machinery |
Pages | 1255-1257 |
Book Title | ASIA CCS '22: proceedings of the 17th Asia Conference on computer and communications security 2022 (ASIA CCS 2022) |
ISBN | 9781450391405 |
DOI | https://doi.org/10.1145/3488932.3527290 |
Keywords | Android; Code vulnerability detection; Static analysis; Vulnerability dataset; Machine learning; Secure mobile apps |
Public URL | https://rgu-repository.worktribe.com/output/1713062 |
SENANAYAKE 2022 Developing secured android
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