An effective genetic algorithm-based feature selection method for intrusion detection systems

Z Halim, MN Yousaf, M Waqas, M Sulaiman… - Computers & …, 2021 - Elsevier
Availability of suitable and validated data is a key issue in multiple domains for
implementing machine learning methods. Higher data dimensionality has adverse effects on …

[HTML][HTML] Android Malware Detection and Identification Frameworks by Leveraging the Machine and Deep Learning Techniques: A Comprehensive Review

SK Smmarwar, GP Gupta, S Kumar - Telematics and Informatics Reports, 2024 - Elsevier
The ever-increasing growth of online services and smart connectivity of devices have posed
the threat of malware to computer system, android-based smart phones, Internet of Things …

Android malware detection based on multi-head squeeze-and-excitation residual network

H Zhu, W Gu, L Wang, Z Xu, VS Sheng - Expert Systems with Applications, 2023 - Elsevier
The popularity and flexibility of the Android platform makes it the primary target of malicious
attackers. The behaviors of malware, such as malicious charges and privacy theft, pose …

[HTML][HTML] A review of deep learning models to detect malware in Android applications

E Mbunge, B Muchemwa, J Batani… - Cyber Security and …, 2023 - Elsevier
Android applications are indispensable resources that facilitate communication, health
monitoring, planning, data sharing and synchronization, social interaction, business and …

[HTML][HTML] An inception V3 approach for malware classification using machine learning and transfer learning

M Ahmed, N Afreen, M Ahmed, M Sameer… - International Journal of …, 2023 - Elsevier
Malware instances have been extremely used for illegitimate purposes, and new variants of
malware are observed every day. Machine learning in network security is one of the prime …

Paired: An explainable lightweight android malware detection system

MM Alani, AI Awad - IEEE Access, 2022 - ieeexplore.ieee.org
With approximately 2 billion active devices, the Android operating system tops all other
operating systems in terms of the number of devices using it. Android has gained wide …

DroidRL: Feature selection for android malware detection with reinforcement learning

Y Wu, M Li, Q Zeng, T Yang, J Wang, Z Fang… - Computers & …, 2023 - Elsevier
Due to the completely open-source nature of Android, the exploitable vulnerability of
malware attacks is increasing. Machine learning, leading to a great evolution in Android …

[HTML][HTML] Feature subset selection for malware detection in smart IoT platforms

J Abawajy, A Darem, AA Alhashmi - Sensors, 2021 - mdpi.com
Malicious software (“malware”) has become one of the serious cybersecurity issues in
Android ecosystem. Given the fast evolution of Android malware releases, it is practically not …

Identifying Disease and Diagnosis in Females Using Machine Learning

S Pramanik, SK Bandyopadhyay - Encyclopedia of Data Science …, 2023 - igi-global.com
Here, the researchers are trying to prepare a model for identifying whether a patient is
diabetic or not. The Pima Indian Dataset has been used in this case study. There are two …

An efficient machine learning-based approach for android v. 11 ransomware detection

I Almomani, A AlKhayer… - 2021 1st international …, 2021 - ieeexplore.ieee.org
Android ransomware is a threatening malware that is targeting individuals and enterprises.
Many existing approaches suggested different ransomware detection solutions to protect …