Machine Learning for a Future-Facing ZTS Revolution

Zero-Trust Security is a cutting-edge technology that starts with Next-Gen Access and enables user verification and device validation, limited access, and provision to learn and adapt. Machine learning is integral to this spearheading security as it quickly detects anomalies while ensuring superior user experience.

A risk-based security strategy, instead of compliance strategy, is the key to machine learning in the context of Zero-Trust Security and it helps to achieve security policy alignment at scale. The algorithms of machine learning detects vulnerabilities and anomalous command runs, and unauthentic resource access histories and accounts.

Machine learning supports Zero-Trust Security by providing enhanced features that brings greater contextual intelligence into authentication, streamlining the experience and increasing user adoption.