[HTML][HTML] MalHyStack: a hybrid stacked ensemble learning framework with feature engineering schemes for obfuscated malware analysis

KS Roy, T Ahmed, PB Udas, ME Karim… - Intelligent Systems with …, 2023 - Elsevier
Since the advent of malware, it has reached a toll in this world that exchanges billions of
data daily. Millions of people are victims of it, and the numbers are not decreasing as the …

[HTML][HTML] GA-StackingMD: Android malware detection method based on genetic algorithm optimized stacking

N Xie, Z Qin, X Di - Applied Sciences, 2023 - mdpi.com
With the rapid development of network and mobile communication, intelligent terminals such
as smartphones and tablet computers have changed people's daily life and work. However …

[HTML][HTML] A machine learning approach for walking classification in elderly people with gait disorders

A Peimankar, TS Winther, A Ebrahimi, UK Wiil - Sensors, 2023 - mdpi.com
Walking ability of elderly individuals, who suffer from walking difficulties, is limited, which
restricts their mobility independence. The physical health and well-being of the elderly …

[HTML][HTML] Android ransomware detection using supervised machine learning techniques based on traffic analysis

A Albin Ahmed, A Shaahid, F Alnasser, S Alfaddagh… - Sensors, 2023 - mdpi.com
In today's digitalized era, the usage of Android devices is being extensively witnessed in
various sectors. Cybercriminals inevitably adapt to new security technologies and utilize …

[HTML][HTML] A study of the relationship of malware detection mechanisms using Artificial Intelligence

J Song, S Choi, J Kim, K Park, C Park, J Kim, I Kim - ICT Express, 2024 - Elsevier
Implementation of malware detection using Artificial Intelligence (AI) has emerged as a
significant research theme to combat evolving various types of malwares. Researchers …

Stacking-based ensemble model for malware detection in android devices

A Joshi, S Kumar - International Journal of Information Technology, 2023 - Springer
Abstract Android Operating Systems (OS) are popular due to their open-source availability
and easy user interface. This makes them vulnerable to various security attacks so it is …

A comprehensive review on permissions-based Android malware detection

Y Sharma, A Arora - International Journal of Information Security, 2024 - Springer
The first Android-ready “G1” phone debuted in late October 2008. Since then, the growth of
Android malware has been explosive, analogous to the rise in the popularity of Android. The …

[HTML][HTML] A lightweight multi-source fast android malware detection model

T Peng, B Hu, J Liu, J Huang, Z Zhang, R He, X Hu - Applied Sciences, 2022 - mdpi.com
Most of the current malware detection methods running on Android are based on signature
and cloud technologies leading to poor protection against new types of malware. Deep …

A formal method for description and decision of android apps behavior based on process algebra

D Liang, L Shen, Z Chen, C Ma, J Feng - IEEE Access, 2022 - ieeexplore.ieee.org
Android is the most popular mobile platform, and it has become a primary malware target.
Existing behavior-based Android malware detection methods suffer from false positive and …

Android malware detection using PMCC heatmap and Fuzzy Unordered Rule Induction Algorithm (FURIA)

NK Kamarudin, A Firdaus, A Zabidi… - Journal of Intelligent …, 2023 - content.iospress.com
Many smart mobile devices, including smartphones, smart televisions, smart watches, and
smart vacuums, have been powered by Android devices. Therefore, mobile devices have …