android-malware-detection

Binary instrumentation framework based on FRIDA

A framework for automated extraction of static and dynamic features from Android applications

Android Mobile Device Hardening

Drebin - NDSS 2014 Re-implementation

Deep Learning for Android Malware Defenses: a SystematicLiterature Review. Android malware detection; Android malware analysis; Deep neural networks; Machine learning

A list of awesome malware detection tools

Android Malware Detection using Deep Learning

A Kotlin Android library for forensics evasion & heuristics evasion that prevents your code from being tested.

Android malware detection using static and dynamic analysis

Android Malware Samples

Android Malware Detection Using Machine Learning Classifiers ( Using Permissions requested by Apps)

⚙️ An efficient tool to do in-depth comparison of two android apps.

Cybersecurity Data Mining Competition 2017

Cybersecurity Data Mining Competition 2016

Android malware classification using both .java files and .so files

CNN based android malware detection system

Detection of Android Malware based on system calls using Support Vector Machines.

Deep Learning Research

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.

Android Malware Detection Website

MAL2 Android-Malware Detection training machine learning detection models and providing API for submitting APK files and getting them analysed

Android Malware Detection with Graph Convolutional Networks using Function Call Graph and its Derivatives.

A static analysis tool for feature extraction from solid apk files

The general goal of this project is to build a web application based on a machine-learning algorithm that can detect fraudulent apps from the Google Play Store or other store using network features values. Demo video: https://www.loom.com/share/29b3ba0b6e644e7d8616c16f88546388

King's College London final dissertation

Implemented a novel Android malware detection software using natural language processing and deep learning to extract features from the static analysis reports of the applications.

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.