Malware detection, analysis and classification

This research topic studies malicious software to determine a given sample’s functionalities, origin and potential impact. The objective is to design automated solutions that may simplify human analysts’ work in detecting malware among legitimate software and recognizing the sample’s families that can be distinguished. Attack vector and functionality are the most characterizing features between malware types. Examples are worms, trojan horses, backdoors, and ransomware which is one the current most impactful threats.

Pra Lab Cybersecurity is currently working on Living-off-the-land LotL(i.e. malware that exploits legitimate software functionalities, like Adobe PDF and Office doc, to execute dangerous activities), x86, and Android malware.