Machine learning is a vast and ever-changing field, and Comodo uses the latest machine learning techniques to determine to
determine if a file is malicious or benign. Comodo has created a predictive model started with collecting a huge number and
variety of malicious and benign files. Features are extracted from files along with the files’ label (e.g. good or bad).
Finally, the model is trained by feeding all of these features to it and allowing it to crunch the numbers and find patterns
and clusters in the data. When the features of a file with an unknown label are presented to the model, it can return a
confidence score of how similar these features are to those of the malicious and benign sets. These concepts underpin
VirusScope, Comodo’s file and behavioral analysis engine residing on the local client.