Sentra enhances its data classification engine with LLMs to tackle data complexity and AI security

Sentra has revealed that Large Language Models (LLM) are now included in its data classification engine, enabling businesses to accurately identify and understand sensitive unstructured data such as employee contracts, source code and user-generated content. With LLMs now integrated directly into Sentra’s data security platform and classification engine, businesses have the technology to proactively reduce the data attack surface.

By clearly understanding the business context of unstructured customer data, Sentra’s new classification approach also allows businesses to better align with compliance criteria, including GDPR, CCPA and HIPAA. This reinforces Sentra’s core mission of providing end-to-end data security no matter where the data resides in multi-cloud environments.

The multi-cloud data landscape makes it difficult for enterprises to accurately classify and create a comprehensive catalog of sensitive unstructured data with meaningful business context. Additionally, companies rushing to harness the power of AI must protect against unauthorized users or applications manipulating LLMs, while ensuring they can detect and respond to training security risks AI models.

“Sentra is committed to innovating and leading the way in enhanced cloud data security to reduce data risks,” said Yoav Regev, CEO of Sentra. “By taking a targeted approach to cloud data security, Sentra gives businesses the confidence to classify large volumes of sensitive enterprise data at scale. With the addition of LLM technology, security teams can more accurately detect sensitive information, allowing them to eliminate data risks where they exist. »

With the growing number of regulatory and privacy frameworks, leveraging LLMs allows Sentra to automatically understand first-party customer data with additional context such as data sovereignty and region, how the data will be used and how it will be used. must be protected. For example, a company might create data security policies that ensure employee agreements are only accessible to HR or that legal contracts are stored on a legal department’s SharePoint site. Ensuring the highest level of security, Sentra only analyzes data with LLM-based classifiers in the company’s cloud premises.

Once a comprehensive data catalog is in place, Sentra’s ability to provide prioritized risk scoring considers multiple layers of data, including data access permissions, activity, sensitivity, movement and configuration errors. This gives businesses greater visibility and control over their data risk management processes.

“As the world continues to explore applications of generative AI and large language models, it is important for the cybersecurity industry to not only innovate with new LLM applications, but also integrate LLM to enhance existing security technologies where applicable,” said Ken Buckler, research analyst at Enterprise Management Associates. “Generative AI holds great potential to improve detection and response to security risks, particularly when it comes to human behavior. While it is important that we move cautiously into this brave new frontier of AI, we must do so urgently as cyber adversaries are also exploring the potential applications of generative AI.

Key developments to Sentra’s classification engine include LLM content analysis of data assets and analysis of metadata, such as file names, schemas and tags. Sentra allows companies to train their LLMs and connect them to Sentra’s classification engine to better classify proprietary data.

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