The evolution of android malware and android analysis techniques

K Tam, A Feizollah, NB Anuar, R Salleh… - ACM Computing …, 2017 - dl.acm.org
With the integration of mobile devices into daily life, smartphones are privy to increasing
amounts of sensitive information. Sophisticated mobile malware, particularly Android …

Android security: a survey of issues, malware penetration, and defenses

P Faruki, A Bharmal, V Laxmi… - … surveys & tutorials, 2014 - ieeexplore.ieee.org
Smartphones have become pervasive due to the availability of office applications, Internet,
games, vehicle guidance using location-based services apart from conventional services …

A multimodal deep learning method for android malware detection using various features

TG Kim, BJ Kang, M Rho, S Sezer… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
With the widespread use of smartphones, the number of malware has been increasing
exponentially. Among smart devices, android devices are the most targeted devices by …

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 …

Reliable third-party library detection in android and its security applications

M Backes, S Bugiel, E Derr - Proceedings of the 2016 ACM SIGSAC …, 2016 - dl.acm.org
Third-party libraries on Android have been shown to be security and privacy hazards by
adding security vulnerabilities to their host apps or by misusing inherited access rights …

Dissecting android malware: Characterization and evolution

Y Zhou, X Jiang - 2012 IEEE symposium on security and …, 2012 - ieeexplore.ieee.org
The popularity and adoption of smart phones has greatly stimulated the spread of mobile
malware, especially on the popular platforms such as Android. In light of their rapid growth …

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 …

User feedback in the appstore: An empirical study

D Pagano, W Maalej - 2013 21st IEEE international …, 2013 - ieeexplore.ieee.org
Application distribution platforms-or app stores-such as Google Play or Apple AppStore
allow users to submit feedback in form of ratings and reviews to downloaded applications. In …

Droidmat: Android malware detection through manifest and api calls tracing

DJ Wu, CH Mao, TE Wei, HM Lee… - 2012 Seventh Asia joint …, 2012 - ieeexplore.ieee.org
Recently, the threat of Android malware is spreading rapidly, especially those repackaged
Android malware. Although understanding Android malware using dynamic analysis can …