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Gen AI security: Enhancing protection through collaboration and trust [Video]

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Based on the integration of artificial intelligence into critical business systems, gen AI security should be top of mind since large language models are vulnerable to various attack vectors.

To mitigate these risks, security and data teams should join hands throughout the AI development lifecycle, laying emphasis on continuous monitoring, input/output controls and early security involvement, according to Steph Hay (pictured, right), head of UX, Google Cloud Security, at Google.

“Being able to collapse the attack surface and enable teams to work together,” Hay stated. “LLMs are uniquely positioned to bring in disparate data that might be, for example, in threat intelligence. We have to add scale, create the kinds of controls on a few different levels to be able to protect the model, the application, the infrastructure and the data. Things against prompt injection, notebook security scanning, being able to monitor all this.”

Hay and Upen Sachdev (left), principal partner at Deloitte & Touche LLP, spoke with theCUBE Research’s

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