This document summarizes different machine learning models for Android malware detection. It introduces Asaf Shabtai as the academic instructor and discusses past problems with malware and solutions. It then presents the prototype detectors for today which include a Byte3g detector using a decision tree model on dex file features, an Anatasia detector using a random forest model on intents, cmd calls, and api calls, a KNN detector using 3NN on permission features, and an SVM detector using an SVM model on api calls and permissions. It concludes by thanking the audience.
