How CrowdStrike Uses SHAP to Enhance Machine Learning Models

CrowdStrike is utilizing SHAP, a Python package implementing Shapley value theory, to enhance the machine learning capabilities of its Falcon platform in detecting malware. By using SHAP, the company can better understand the predictive power of its models by quantifying how individual feature values influence predictions, providing insights into whether a feature makes a file appear "cleaner" or "dirtier." This approach aids in feature engineering by allowing security analysts to craft specific features for new malware families and assess their significance in classification. The process streamlines model updates, ensuring faster deployment of protections and enhancing the robustness and intuitive nature of feature use. Through this integration of open-source tools and CrowdStrike’s extensive data streams, the company aims to improve its machine learning models' generalization capabilities, thereby strengthening malware detection and prevention efforts.