… permission and API calls which an app demand at the time of … using machine learning
techniques, our framework can be easily differentiated between benign or malware-infected apps…

… environments and the machine learning models. Then, Section V presents the trending
Bangladeshi apps analyzed in this study. We present the result of our analysis in Section VI and …

… Moreover this paper uses machine learning because non machine learning approaches
are non-reliable and not efficient. In existing approaches only 30 permissions out of 300 …

… In this subsection, we discuss about the analysis and its types which are used for Android …
from Android. In this study, we perform dynamic analysis of Android apps to build a malware …

… This work investigates Android botnets using static analysis to … The features are then used
to develop effective machine learning … The features are extracted from 1928 Android botnet …

… software variants (MSV) in Android Apps that use the Gated Recurrent Unit [GRU] [ANN…
deep learning methods is provided in order to identify the most effective model to identify Android …

… Android malware detection. Moreover, this paper defines and further illustrates the four classes
of android … proposing a static analysis-based malware detection method with this recent …

… This paper surveys the state of the art on Android malware, and malware detection techniques
by focusing on Machine Learning- based algorithms used to detect malware on Android …

… extract the permissions from an app. Based on this cognition … method based on TF-IDF and
Machine Learning is proposed. The system permissions are extracted in Android application …

… on android smartphones. In this paper, an intelligent model using machine learning algorithms
is … in smartphones based on the static malware analysis technique. The contents of an …