Antivirus applied to JAR malware detection based on runtime behaviors.

Java vulnerabilities correspond to 91% of all exploits observed on the worldwide web. The present work aims to create antivirus software with machine learning and artificial intelligence and master in Java malware detection. Within the proposed methodology, the suspected JAR sample is executed to intentionally infect the Windows OS monitored in a controlled environment.