Accurately labeling apps as malicious and benign is fundamental for training effective and reliable ML-based malware detection methods. The infeasibility of manually labeling apps forces researchers to rely on online platforms, such as VirusTotal, to label apps. Unfortunately, such platforms are often volatile and dynamic. The main objective of this thesis is to provide the research community with methods to optimally utilize VirusTotal scan reports until a more stable, reliable platform is implemented.     «

Accurately labeling apps as malicious and benign is fundamental for training effective and reliable ML-based malware detection methods. The infeasibility of manually labeling apps forces researchers to rely on online platforms, such as VirusTotal, to label apps. Unfortunately, such platforms are often volatile and dynamic. The main objective of this thesis is to provide the research community with methods to optimally utilize VirusTotal scan reports until a more stable, reliable platform is impl...     »