CrowdStrike Researchers Explore Contrastive Learning to Enhance Detection Against Emerging Malware Threats
The process of crafting new malware detection features is usually time-consuming and requires extensive domain knowledge outside the expertise of many machine learning practitioners. These factors make it especially difficult to keep up with a constantly evolving threat landscape. To mitigate these challenges, the CrowdStrike Data Science team explored the use of deep learning to automatically generate features for novel malware families.