Data on Vulnerability Detection in Android

Data in Brief
Shivi Garg, Niyati Baliyan

Abstract

The data in this article have been collaborated from mainly four sources- Google Playstore, Wandoujia (third party app store market), AMD and Androzoo. These data include ~85,000 APKs (Android Package Kit), both malicious and benign from these data sources. Static and dynamic features are extracted from these APK files, and then supervised machines learning algorithms are employed for malware detection in Android. This data article also provides the Python code for data analysis. For feature extraction, a generic algorithm has also been incorporated, thereby, selecting important and relevant feature subset. Conclusive results obtained from this data set are further comprehended and interpreted in our latest research study "A Novel Parallel Classifier Scheme for Vulnerability Detection in Android" (Garg et al., 2018). This proved to be precious contribution for ensembling classifiers in machine learning to detect malware in Android.

Methods Mentioned

BETA
feature extraction

Software Mentioned

Android Debug Bridge ( ADB ) shell
Google Play store
Gradle
Android AMD Malware
Androids
Android Studio
Android emulator
Chrome
Python script
APKTool

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