Machine learning and deep learning techniques for detecting malicious android applications: An empirical analysis

P Bhat, S Behal, K Dutta - Proceedings of the Indian National Science …, 2023 - Springer
The open system architecture of android makes it vulnerable to a variety of cyberattacks.
Cybercriminals use android applications to intrude into the system and steal confidential …

[PDF][PDF] Outsmarting Android Malware with Cutting-Edge Feature Engineering and Machine Learning Techniques.

A Wajahat, J He, N Zhu, T Mahmood… - … , Materials & Continua, 2024 - researchgate.net
The growing usage of Android smartphones has led to a significant rise in incidents of
Android malware and privacy breaches. This escalating security concern necessitates the …

DCEL: Classifier Fusion Model for Android Malware Detection

X Xu, S Jiang, J Zhao, X Wang - Journal of Systems …, 2024 - ieeexplore.ieee.org
The rapid growth of mobile applications, the popularity of the Android system and its
openness have attracted many hackers and even criminals, who are creating lots of Android …

Android Malware Analysis using Coefficient of Multiple Correlation

S Jain, S Kapoor, A Arora… - 2023 IEEE Symposium …, 2023 - ieeexplore.ieee.org
Android being the most famous Operating System (OS) for smart hand-held devices also
serves as a prime attraction for cyber-criminals and black hat hackers. Hacking into these …

Optimizing Android Program Malware Classification Using GridSearchCV Optimized Random Forest

L Hakim, Z Sari, AR Aristyo… - Kinetik: Game Technology …, 2024 - kinetik.umm.ac.id
The growing number of smartphones, particularly Android powered ones, has increased
public awareness of the security concerns posed by malware and viruses. While machine …