DeepAMD: Detection and identification of Android malware using high-efficient Deep Artificial Neural Network

SI Imtiaz, S ur Rehman, AR Javed, Z Jalil, X Liu… - Future Generation …, 2021 - Elsevier
Android smartphones are being utilized by a vast majority of users for everyday planning,
data exchanges, correspondences, social interaction, business execution, bank …

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 …

Droiddetectmw: A hybrid intelligent model for android malware detection

F Taher, O AlFandi, M Al-kfairy, H Al Hamadi… - Applied Sciences, 2023 - mdpi.com
Malicious apps specifically aimed at the Android platform have increased in tandem with the
proliferation of mobile devices. Malware is now so carefully written that it is difficult to detect …

A hybrid feature selection approach-based Android malware detection framework using machine learning techniques

SK Smmarwar, GP Gupta, S Kumar - Cyber Security, Privacy and …, 2022 - Springer
With more popularity and advancement in Internet-based services, the use of the Android
smartphone has been increasing very rapidly. The tremendous popularity of using the …

Android malware category and family detection and identification using machine learning

AHE Fiky, AE Shenawy, MA Madkour - arxiv preprint arxiv:2107.01927, 2021 - arxiv.org
Android malware is one of the most dangerous threats on the internet, and it's been on the
rise for several years. Despite significant efforts in detecting and classifying android malware …

[HTML][HTML] A novel feature selection technique: Detection and classification of Android malware

S Sharma, R Chhikara, K Khanna - Egyptian Informatics Journal, 2025 - Elsevier
Android operating system is not just the most commonly employed mobile operating system,
but also the most lucrative target for cybercriminals due to its extensive user base. In light of …

IPAnalyzer: A novel Android malware detection system using ranked Intents and Permissions

Y Sharma, A Arora - Multimedia Tools and Applications, 2024 - Springer
Android malware has been growing in scale and complexity, spurred by the unabated
uptake of smartphones worldwide. Millions of malicious Android applications have been …

[HTML][HTML] CIAA-RepDroid: a fine-grained and probabilistic reputation scheme for android apps based on sentiment analysis of reviews

F Tchakounté, AE Yera Pagor, JC Kamgang… - Future Internet, 2020 - mdpi.com
To keep its business reliable, Google is concerned to ensure the quality of apps on the store.
One crucial aspect concerning quality is security. Security is achieved through Google Play …

PHIGrader: Evaluating the effectiveness of Manifest file components in Android malware detection using Multi Criteria Decision Making techniques

Y Sharma, A Arora - Journal of Network and Computer Applications, 2024 - Elsevier
The popularity of the Android operating system has itself become a reason for privacy
concerns. To deal with such malware threats, researchers have proposed various detection …

Family Classification of Malicious Applications using Hybrid Analysis and Computationally Economical Machine Learning Techniques

P Kishore, SK Barisal… - 2022 IEEE/WIC/ACM …, 2022 - ieeexplore.ieee.org
Most users utilize android smartphones for almost all activities. However, malicious attacks
on these devices rose exponentially. Samples can be classified accurately, but earlier …