Detection approaches for android malware: Taxonomy and review analysis

HHR Manzil, SM Naik - Expert Systems with Applications, 2023 - Elsevier
The main objective of this review is to present an in-depth study of Android malware
detection approaches. This article provides a comprehensive survey of 150 studies on …

Malware detection using deep learning and correlation-based feature selection

ES Alomari, RR Nuiaa, ZAA Alyasseri, HJ Mohammed… - Symmetry, 2023 - mdpi.com
Malware is one of the most frequent cyberattacks, with its prevalence growing daily across
the network. Malware traffic is always asymmetrical compared to benign traffic, which is …

A system call-based android malware detection approach with homogeneous & heterogeneous ensemble machine learning

P Bhat, S Behal, K Dutta - Computers & Security, 2023 - Elsevier
The enormous popularity of Android in the smartphone market has gained the attention of
malicious actors as well. Also, considering its open system architecture, malicious attacks …

[HTML][HTML] DL-AMDet: Deep learning-based malware detector for android

AR Nasser, AM Hasan, AJ Humaidi - Intelligent Systems with Applications, 2024 - Elsevier
The Android operating system, with its market share leadership and open-source nature in
smartphones, has become the primary target of malware. However, detecting malicious …

Metaheuristics with deep learning model for cybersecurity and Android malware detection and classification

A Albakri, F Alhayan, N Alturki, S Ahamed… - Applied Sciences, 2023 - mdpi.com
Since the development of information systems during the last decade, cybersecurity has
become a critical concern for many groups, organizations, and institutions. Malware …

An integral cybersecurity approach using a many-objective optimization strategy

O Salinas, R Soto, B Crawford, R Olivares - IEEE Access, 2023 - ieeexplore.ieee.org
Data networks and computing devices have experienced exponential growth. Within a short
span of time, they have opened new digital frontiers while also bringing forth new threats …

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 …

[PDF][PDF] Android-manifest extraction and labeling method for malware compilation and dataset creation.

D Hindarto, A Djajadi - International Journal of Electrical & Computer …, 2023 - academia.edu
Malware is a nuisance for smartphone users. The impact is detrimental to smartphone users
if the smartphone is infected by malware. Malware identification is not an easy process for …

XAI-AMD-DL: An explainable AI approach for android malware detection system using deep learning

SK Smmarwar, GP Gupta… - 2023 IEEE World …, 2023 - ieeexplore.ieee.org
Efficient malware identification is essential to safe the system resources and privacy of data
for cybersecurity system. The use of android smartphones has increased tremendously that …

BRL-ETDM: Bayesian reinforcement learning-based explainable threat detection model for industry 5.0 network

AK Dey, GP Gupta, SP Sahu - Cluster Computing, 2024 - Springer
To enhance the universal adaptability of the Real-Time deployment of Industry 5.0, various
machine learning-based cyber threat detection models are given in the literature. Most of the …