Ways in which AI And Machine Learning Are Improving Endpoint Security

Machine learning is automating the more manually-based, routine incident analysis, and escalation tasks that are overwhelming security analysts today. Capitalizing on supervised machine learnings' innate ability to fine-tune algorithms in milliseconds based on the analysis of incidence data, endpoint security providers are prioritizing this area in product development. Performing real-time scans of all processes with an unknown or suspicious reputation is another way how machine learning is improving endpoint security. Commonly referred to as Hunt and Respond, supervised and unsupervised machine learning algorithms are being used today to seek out and resolve potential threats in milliseconds instead of days. Machine learning is accelerating the consolidation of endpoint security technologies, a market dynamic that is motivating organizations to trim back from the ten clients they have on average per endpoint today.