Abstract: The increasing number of malicious software spread through the Internet has become a serious threat. Malware authors use obfuscation and deformation techniques to generate new types of ...

In this work, a decision tree based Android malware detection system was developed using C4.5 and Hoeffding tree algorithms. In the developed system, the success rate of the C4.5 decision tree ...

The authors’ approach is based on differences between assembly op-code frequencies in malware and benign classes. They have also utilized decision tree algorithms to simplify the classification.

This project explores the application of AI models to classify and detect malware, offering a modern approach to bolster cybersecurity defenses. Implemented supervised learning models (Decision Tree ...