A framework for automated extraction of static and dynamic features from Android applications
-
Updated
Dec 7, 2022 - Python
A framework for automated extraction of static and dynamic features from Android applications
Android Mobile Device Hardening
Drebin - NDSS 2014 Re-implementation
Android Malware Detection using Deep Learning
Android malware detection using static and dynamic analysis
⚙️ An efficient tool to do in-depth comparison of two android apps.
Cybersecurity Data Mining Competition 2016
Android malware classification using both .java files and .so files
Cybersecurity Data Mining Competition 2017
Android Malware Detection Website
Phenax is an open source framework to test Android applications whether they are malicious or not. Using a tool called GroddDroid and machine learning algorithms this framework repeatedly runs a number of goodware and malware applications forcing a different execution path in each application in each run.
Storehouse of scripts/code snippets corresponding to the current RnD project.
Deep Learning Research
King's College London final dissertation
Given a library of smali files from an APK which have been manually renamed after analysis, it can take the same library from a different APK which was decompiled with proguard and by comparing the two libraries will re-name the new smali library files to match the known naming of the original.
Build ensmbled Android Malware Classifier by using stacking-like method.
Dissertation
Android malware classification system
Android applications extraction system - Extract static feature of list android applications
Add a description, image, and links to the android-malware-detection topic page so that developers can more easily learn about it.
To associate your repository with the android-malware-detection topic, visit your repo's landing page and select "manage topics."