The State of ML in Cybersecurity
Crowdstrike Article While AI is on the rise and seems to be unstoppable, its applications to threat detection—specifically in cybersecurity—have yet to show great promise. Traditional approaches to applying machine learning to threat detection overlook some important factors. The first is the sheer amount of data required to train a reliable detection model. While there is no shortage of data in areas like memory usage, CPU usage, file changes, and other system activity, the data for successfully flagging actual malicious behavior—especially malware executions—is sparse. ...