Protecting private patient data is critical for any healthcare organization. From securing systems from outside hackers to monitoring and controlling internal access, there are a multitude of steps any organization can take to better protect PHI and EMR data. See Also: OnDemand Fireside Chat Zero Tolerance: Controlling The Landscape Where You'll Meet Your Adversaries One of the recent developments in this arena is machine learning driven access monitoring. Unlike traditional, rules-based access monitoring, this new, more adaptive technology is changing how organizations monitor, assess, and control access. Access monitoring is exactly what it sounds like -- monitoring user access to network resources, critical data, and high-risk access points.

Employee identities are the new security perimeter of any business. According to the Verizon Mobile Security Index 2018 Report, 89% of organizations are relying on just a single security strategy to keep their mobile networks safe. And with Gartner predicting worldwide security spending reaching $96B this year, up 8% from 2017, it's evident enterprises must adopt a more vigilant, focused strategy for protecting every threat surface and access point of their companies. IT security strategies based on trusted and untrusted domains are being rendered insufficient as hackers camouflage their attacks through compromised, privileged credentials. It's happening so often that eight in ten breaches are now the result of compromised employee identities.