7 stories
A robot arm doesn’t care where the server lives There is no single safest option. Cloud, on-premises and hybrid setups can all protect robotics systems well. They just split responsibility differently, and most factories end up blending them. Sounds neat on paper. In practice, it’s messy.
For enterprises, data resiliency ultimately comes down to an ability for useful work to continue. The definition sounds simple, yet making sure that data in critical systems is fully protected and accessible as rapidly as possible is a complicated task.
The practice of building cybersecurity directly into networks and databases has taken on greater importance in the new era of agentic AI. Trust boundaries are being relocated to the database itself, where access policies can be enforced regardless of the instructions an AI agent has received.
AI agent access is complicating identity controls as agents log in, carry credentials and act on someone’s behalf. They have characteristics of both human and machine users.
Security operations teams are changing their approach in the world of artificial intelligence, adopting automation to turn signals into outcomes while maintaining the right context and control.
Confidential AI means running a model on infrastructure that has no ability to read what it's processing. Data has been encrypted at rest and in transit for decades — but computing on it requires decrypting it into host memory first.
Explore the core domains of cybersecurity, major threat paths, practical defense-in-depth controls, and the trends shaping digital risk management.
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