Uma GUI para hackers do bem aprenderem sobre malwares sintéticos

Abstract

Ethical hackers need to constantly stay updated to combat emerging techniques used by malicious hackers. This includes the use of deep learning to create new Android malware that mimics the behavior of legitimate applications, aiming to deceive antivirus systems while exploiting newly discovered vulnerabilities. In this context, we developed Malware DataLab, a platform focused on teaching deep learning techniques with the goal of expanding Android malware datasets using synthetic data. This work presents the graphical interface of MalSynGen, the tool for generating synthetic tabular data within the Malware DataLab. A preliminary experimental evaluation demonstrates the positive impact of the proposal.