How Generative AI is a Game Changer for Cloud Security

Generative AI will mark an inflection point in cloud security, especially in common pain points such as threat prevention, reducing fatigue from repetitive tasks, and closing the cybersecurity talent gap.

An image representing cloud servers.
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Cloud security and AI have a long-term partnership. For nearly a decade, AI has been used to identify threats and prioritize risks in the cloud through its pattern recognition and anomaly detection capabilities.

However, a lot has changed in the past 10 years. With more people and organizations migrating to cloud applications, threat actors have followed, seeing cloud applications as a prime target.

Cloud security is more important than ever to an organization’s cybersecurity maturity, and integrating AI into cloud security tools is a vital layer of defense against an expanding cloud-based threat landscape. Now, one of the biggest game changers for cloud security is generative AI, according to Google.

Generative AI has the potential to reduce the drudgery of repetitive tasks facing security teams, such as aggregating and enriching data from a multitude of sources to gain a more comprehensive understanding of risks and where to focus, Sunil Potti, VP/GM of Google Cloud Security, said in a recent blog post as part of the Google Cloud Security Summit in June.

Google’s cloud security efforts include AI Workbench, where artificial intelligence will be used to address and prevent emerging threats, eliminate threat fatigue fatigue caused by alert overload, and close the talent gap.

SEE: Here’s an in-depth look at how generative AI works.

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Building on the role of AI in cloud security

Traditionally, AI has been used to detect and remediate hundreds of threats in seconds.

Generative AI takes AI to a new level because it focuses on creating new data rather than simply analyzing existing data. [Generative AI] it enables the development of realistic synthetic data, which can be used to train and test security models without exposing sensitive information, Bob Janssen, vice president of engineering and head of innovation at Delinea, told TechRepublic.

Generative AI is a game changer in how organizations approach cloud security, said Janssen. It provides realistic synthetic data for testing, simulates sophisticated attack scenarios, and minimizes the risk of exposing sensitive information during development, improving overall security measures, he added.

How Generative AI Affects Cloud Security

What distinguishes Generative AI from the AI ​​models currently used in cloud security is its ability to summarize, classify, and generate information. With proper training, it can reason on specialized data and provide natural language conversational interactions that facilitate workflows faster than the flat interfaces in typical security tools.

These cloud security-applied features enable customers to identify and prioritize the risks most relevant to their unique environment or regulatory requirements; to quickly generate the queries and detections needed to continuously monitor for threats, Potti said. Generative AI can be used to interact in natural language with an assistive experience that can guide clients towards their ideal outcomes.

At Google, for example, cloud security is augmented with generative AI so customers can search petabytes of event data using natural language instead of writing custom queries. Another feature provides a human-readable explanation of potential attack paths and steps to remediate.

So with AI, it’s still in its infancy, Potti said, but we’re leveraging these superpowers for security achievements like early detection of breaches or instant classification of potential malware.

Read ahead: A fundamental guide to cloud security.

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