Shielding Android: Malware Detection with Machine Learning

DOI

10.2991/978-94-6239-693-7_102How to use a DOI?

Keywords

Android Malware Detection; Voting Classifier; Linear Discriminant Analysis (LDA); Quadratic Discriminant Analysis (QDA); Machine Learning; Feature Extraction; Security Threats; Mobile Security; Malware Classification; Proactive Protection

Abstract

Android platforms are gaining popularity and hence, they have become the popular victims of viral attacks. The project is an undertaking dealing with malware detector system development. The android application and the Voting Classifier algorithm which uses the Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA). The system enhances the tolerance in the detection of malicious applications by integration. The operations of the non-linear decision-making and the linear decision-making models. A strong handles these application data in the system processing pipeline which enables extraction of features of high quality. A consensus between the LDA and QDA model is then employed to classify. Android applications as harmless or malicious making use of the Voting. Classifier. The measures of the system performance are based on some. The metrics that are used are accuracy, precision, recall and F1-score that provides a legitimate strategy in the identification of any potential security threat. This iis a highspeed and effective, lightweight protection system capable of securing. Malware are proactive Android and offer them a superior security mobile users.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - K. S. Joy Andrew
AU  - A. Manigandan
AU  - D. Jerusha
PY  - 2026
DA  - 2026/06/16
TI  - Shielding Android: Malware Detection with Machine Learning
BT  - Proceedings of the International Conference on Intelligent Systems for a Sustainable Future (ISSF 2026)
PB  - Atlantis Press
SP  - 1056
EP  - 1068
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-693-7_102
DO  - 10.2991/978-94-6239-693-7_102
ID  - Andrew2026
ER  -