Data security and AI: Speed and protection in cloud migration – SiliconANGLE News

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As artificial intelligence solutions swiftly advance and the trend toward cloud data migration continues, data leaders must balance priorities between data security, agility and visibility.

Concurrently, there is a growing concern among many about the wider security implications that AI might have on their organization. AI is the ultimate data product, and companies need to consider protecting its data within AI as they use it to accelerate business decisions, according to Paul Hawkins (pictured), chief information security officer of CipherStash Pty Ltd.

“Businesses really want to use AI and large language models to accelerate their business decisions. It makes a lot of things really easy,” he said. “You can kind of put some prompts in and get some information back, and then you can make decisions based on that. But at the same time, it’s actually a really traditional problem. Having visibility of where your data is and what systems are using that data is something we’ve been doing in the security industry for a really long time.”

Hawkins spoke with theCUBE Research principal analyst Rob Strechay at the “Supercloud 6: AI Innovators” event, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed the need for organizations to prioritize securing their data within AI to accelerate business decisions.

Data security in the enterprise: A speed and data protection balancing act

Balancing the need for speed with strong data protection and governance is crucial for organizations, according to Hawkins. Building a decision-making framework that allows engineers to use data without having to figure out how to protect it every time is essential.

As society uses more data, it becomes important to identify normal and abnormal usage patterns, especially in applications such as in the medical field, where abnormal data movement can be detected by monitoring data operations, Hawkins explained. Protecting data in a data lake is crucial, as the risk profile changes when aggregating data from different databases. CISOs should consider securing their data and AI in the future.

“Being able to have the protection move with the data is really valuable. You have a greater degree of confidence that when business teams join all of these data sets together, you still have the level of confidence that it’s protected,” Hawkins said. “The business can still reach its outcome by doing queries on large data sets and getting insights from them without leaking individual records.”

Security foundations are important for building secure applications and making good decisions, especially in the context of large language model security, according to Hawkins. Everyone is in the same boat, so it’s important for CISOs to take advice to heart and paddle in the same direction.

“Being really clear about what you’re trying to solve and basing that on really good security foundations means that we can take advantage of the really fast development of AI,” Hawkins added. “We can accelerate our businesses while still keeping the data that we build our businesses on protected and safe, and then we can all kind of move fast.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE Research’s coverage of the “Supercloud 6: AI Innovators” event:

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Photo: SiliconANGLE

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