A survey of app store analysis for software engineering

W Martin, F Sarro, Y Jia, Y Zhang… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
App Store Analysis studies information about applications obtained from app stores. App
stores provide a wealth of information derived from users that would not exist had the …

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 …

Malware analysis in IoT & android systems with defensive mechanism

CS Yadav, J Singh, A Yadav, HS Pattanayak, R Kumar… - Electronics, 2022 - mdpi.com
The Internet of Things (IoT) and the Android operating system have made cutting-edge
technology accessible to the general public. These are affordable, easy-to-use, and open …

Droidcat: Effective android malware detection and categorization via app-level profiling

H Cai, N Meng, B Ryder, D Yao - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Most existing Android malware detection and categorization techniques are static
approaches, which suffer from evasion attacks, such as obfuscation. By analyzing program …

[PDF][PDF] Drebin: Effective and explainable detection of android malware in your pocket.

D Arp, M Spreitzenbarth, M Hubner, H Gascon… - Ndss, 2014 - media.telefonicatech.com
Malicious applications pose a threat to the security of the Android platform. The growing
amount and diversity of these applications render conventional defenses largely ineffective …

Yes, machine learning can be more secure! a case study on android malware detection

A Demontis, M Melis, B Biggio… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
To cope with the increasing variability and sophistication of modern attacks, machine
learning has been widely adopted as a statistically-sound tool for malware detection …

Semantics-aware android malware classification using weighted contextual api dependency graphs

M Zhang, Y Duan, H Yin, Z Zhao - … of the 2014 ACM SIGSAC conference …, 2014 - dl.acm.org
The drastic increase of Android malware has led to a strong interest in developing methods
to automate the malware analysis process. Existing automated Android malware detection …

Droidapiminer: Mining api-level features for robust malware detection in android

Y Aafer, W Du, H Yin - Security and Privacy in Communication Networks …, 2013 - Springer
The increasing popularity of Android apps makes them the target of malware authors. To
defend against this severe increase of Android malwares and help users make a better …

[PDF][PDF] Copperdroid: Automatic reconstruction of android malware behaviors.

K Tam, SJ Khan, A Fattori, L Cavallaro - Ndss, 2015 - core.ac.uk
Mobile devices and their application marketplaces drive the entire economy of the today's
mobile landscape. Android platforms alone have produced staggering revenues, exceeding …

PermPair: Android Malware Detection Using Permission Pairs

A Arora, SK Peddoju, M Conti - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
The Android smartphones are highly prone to spreading the malware due to intrinsic
feebleness that permits an application to access the internal resources when the user grants …