A review on feature selection in mobile malware detection

A Feizollah, NB Anuar, R Salleh, AWA Wahab - Digital investigation, 2015 - Elsevier
The widespread use of mobile devices in comparison to personal computers has led to a
new era of information exchange. The purchase trends of personal computers have started …

Comprehensive review and analysis of anti-malware apps for smartphones

M Talal, AA Zaidan, BB Zaidan, OS Albahri… - Telecommunication …, 2019 - Springer
The new and disruptive technologies for ensuring smartphone security are very limited and
largely scattered. The available options and gaps in this research area must be analysed to …

Madam: Effective and efficient behavior-based android malware detection and prevention

A Saracino, D Sgandurra, G Dini… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
Android users are constantly threatened by an increasing number of malicious applications
(apps), generically called malware. Malware constitutes a serious threat to user privacy …

Evaluation of machine learning classifiers for mobile malware detection

FA Narudin, A Feizollah, NB Anuar, A Gani - Soft Computing, 2016 - Springer
Mobile devices have become a significant part of people's lives, leading to an increasing
number of users involved with such technology. The rising number of users invites hackers …

A multimodal malware detection technique for Android IoT devices using various features

R Kumar, X Zhang, W Wang, RU Khan, J Kumar… - IEEE …, 2019 - ieeexplore.ieee.org
Internet of things (IoT) is revolutionizing this world with its evolving applications in various
aspects of life such as sensing, healthcare, remote monitoring, and so on. Android devices …

DroidMalwareDetector: A novel Android malware detection framework based on convolutional neural network

AT Kabakus - Expert Systems with Applications, 2022 - Elsevier
Smartphones have become an integral part of our daily lives thanks to numerous reasons.
While benefitting from what they offer, it is critical to be aware of the existence of malware in …

Dendroid: A text mining approach to analyzing and classifying code structures in android malware families

G Suarez-Tangil, JE Tapiador, P Peris-Lopez… - Expert Systems with …, 2014 - Elsevier
The rapid proliferation of smartphones over the last few years has come hand in hand with
and impressive growth in the number and sophistication of malicious apps targetting …

A taxonomy and qualitative comparison of program analysis techniques for security assessment of android software

A Sadeghi, H Bagheri, J Garcia… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
In parallel with the meteoric rise of mobile software, we are witnessing an alarming
escalation in the number and sophistication of the security threats targeted at mobile …

Black-box Adversarial Example Attack towards {FCG} Based Android Malware Detection under Incomplete Feature Information

H Li, Z Cheng, B Wu, L Yuan, C Gao, W Yuan… - 32nd USENIX Security …, 2023 - usenix.org
The function call graph (FCG) based Android malware detection methods have recently
attracted increasing attention due to their promising performance. However, these methods …

ANASTASIA: ANdroid mAlware detection using STatic analySIs of Applications

H Fereidooni, M Conti, D Yao… - 2016 8th IFIP …, 2016 - ieeexplore.ieee.org
The number of malware applications targeting the Android operating system has
significantly increased in recent years. Malicious applications pose a significant threat to …