Machine Learning Assisted Threat Prevention

Use Case Description

Sometimes, no matter how broad of a net is cast with heuristics, signatures just aren’t enough to capture all malware. Machine learning provides an adaptive solution to these elusive corner cases. By learning from their mistakes, ML classifiers are able to tightly fill the cracks in a system’s armor.

Our Solution

InQuest’s proprietary machine learning software is built out of four well-vetted classifiers, and uses previously collected data on malicious and benign content to automatically discover patterns that might be left uncovered by signatures. On a weekly basis, models constructed from our ML algorithms are updated with the latest information from previously processed network traffic.