Putting AI To Practical Use In Cybersecurity - AI Summary

"AI is performing well in back-end processing of security events, allowing for automation and speed of use-case development," says Doug Saylors, partner and cybersecurity co-lead with global technology research and advisory firm ISG. This is crucial because "in modern environments, ephemeral cloud assets turn on and off in minutes, work-from-home devices are hidden from view, and data centers are full of dusty corners," says Rosiek. "In what's being called XDR, AI/ML is just another tool in the toolbox to find anomalies -- methods of attack that aren't caught by traditional defense-in-depth technologies," says Patrick Orzechowski, vice president and distinguished engineer at managed cybersecurity vendor Deepwatch. "In cybersecurity, this is best reflected in areas such as intrusion detection and network monitoring -- it's fairly safe for administrators to allow AI to discover activity that is an outlier and may be malicious in these cases" says Sean O'Brien, founder and lead researcher at Privacy Lab at Yale and CSO at privacy-focused chat company Panquake. Cyber AI is "very hard," warns Aaron Sant-Miller, chief data scientist at consulting firm Booz Allen Hamilton, but it is key to building effective defenses.