The evolution of android malware and android analysis techniques
With the integration of mobile devices into daily life, smartphones are privy to increasing
amounts of sensitive information. Sophisticated mobile malware, particularly Android …
amounts of sensitive information. Sophisticated mobile malware, particularly Android …
A review on feature selection in mobile malware detection
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 …
new era of information exchange. The purchase trends of personal computers have started …
Apposcopy: Semantics-based detection of android malware through static analysis
We present Apposcopy, a new semantics-based approach for identifying a prevalent class of
Android malware that steals private user information. Apposcopy incorporates (i) a high …
Android malware that steals private user information. Apposcopy incorporates (i) a high …
Android malware familial classification and representative sample selection via frequent subgraph analysis
The rapid increase in the number of Android malware poses great challenges to anti-
malware systems, because the sheer number of malware samples overwhelms malware …
malware systems, because the sheer number of malware samples overwhelms malware …
Andrubis--1,000,000 apps later: A view on current Android malware behaviors
M Lindorfer, M Neugschwandtner… - … on building analysis …, 2014 - ieeexplore.ieee.org
Android is the most popular smartphone operating system with a market share of 80%, but
as a consequence, also the platform most targeted by malware. To deal with the increasing …
as a consequence, also the platform most targeted by malware. To deal with the increasing …
Automated poisoning attacks and defenses in malware detection systems: An adversarial machine learning approach
The evolution of mobile malware poses a serious threat to smartphone security. Today,
sophisticated attackers can adapt by maximally sabotaging machine-learning classifiers via …
sophisticated attackers can adapt by maximally sabotaging machine-learning classifiers via …
HelDroid: Dissecting and Detecting Mobile Ransomware
In ransomware attacks, the actual target is the human, as opposed to the classic attacks that
abuse the infected devices (eg, botnet renting, information stealing). Mobile devices are by …
abuse the infected devices (eg, botnet renting, information stealing). Mobile devices are by …
Achieving accuracy and scalability simultaneously in detecting application clones on android markets
Besides traditional problems such as potential bugs,(smartphone) application clones on
Android markets bring new threats. That is, attackers clone the code from legitimate Android …
Android markets bring new threats. That is, attackers clone the code from legitimate Android …
Finding unknown malice in 10 seconds: Mass vetting for new threats at the {Google-Play} scale
An app market's vetting process is expected to be scalable and effective. However, today's
vetting mechanisms are slow and less capable of catching new threats. In our research, we …
vetting mechanisms are slow and less capable of catching new threats. In our research, we …
A performance-sensitive malware detection system using deep learning on mobile devices
Currently, Android malware detection is mostly performed on server side against the
increasing number of malware. Powerful computing resource provides more exhaustive …
increasing number of malware. Powerful computing resource provides more exhaustive …