News Report Software
November 28, 2023

Privacera AI Governance Integrates with AWS to Bolster Generative AI Model Security

Privacera AI Governance Integrates with AWS to Bolster Generative AI Model Security

AI and data security governance firm Privacera recently announced that its Privacera AI Governance (PAIG) now integrates with Amazon Web Services (AWS) to fortify security measures for foundational models (FMs) utilized in generative AI applications.

The company said PAIG is designed to responsibly govern and safeguard sensitive data within FMs and generative AI applications, and leverages the capabilities of Amazon Bedrock and Amazon SageMaker.

Amazon Bedrock is AWS’s fully-managed service facilitating access to FMs from leading AI companies through an API, teams up with PAIG to build and scale generative AI applications. Simultaneously, Amazon SageMaker, a cloud-based machine-learning platform, enables the creation, training, and deployment of machine learning (ML) models on the cloud, supporting both open-source and proprietary FMs and workflows.

“For many organizations, AWS is the preferred platform to run and scale AI and generative AI applications. Increasingly, organizations are realizing conforming to data security and governance mandates become a critical hurdle to the mainstream deployment of these new apps,” Balaji Ganesan, co-founder and CEO of Privacera told Metaverse Post.

“PAIG integrates with Amazon Bedrock to provide real-time security and privacy for all user inputs and model responses to ensure no sensitive or personal data is accidentally loaded into the app or disclosed by the app,” he added.

The security platform provides fine-grained auditing and monitoring to enable compliance reporting. Moreover, PAIG is built on Privacera’s Data Security Platform that provides integration and security across the entire AWS data estate with support for Lake Formation and other AWS data services.

“One of the unique capabilities of PAIG is to enforce security in real time using our policy orchestration framework as part of our Data Security Platform. This means that your policies can be enforced across multiple applications without hard coding security rules in each application,” said Privacera’s Ganesan. “That ensures consistency and auditability across all your generative AI applications and models.”

Easing Generative AI Development with Data Security and Privacy

PAIG furnishes a comprehensive suite of built-in product capabilities to address privacy, security and compliance requirements linked with building generative AI applications. Whether utilizing open-source, public FMs or customizing private FMs, Privacera said PAIG ensures consistent security controls throughout the entire lifecycle of generative AI applications.

The integrated solution provides security and governance capabilities covering the end-to-end lifecycle of generative AI applications, including discovery, training, deployment, and continuous monitoring. The security platform analyzes user-injected model inputs and outputs to detect sensitive data in AI model output and input, blocking or masking unauthorized data.

Likewise, PAIG can also monitor user interactions with AI models, offering dashboards for visibility across all generative AI applications and models, detailing requests made, sensitive data identified and actions taken to protect sensitive data. A comprehensive audit trail is also provided to track individual user activities.

“PAIG is a model-agnostic service that seamlessly embeds into your generative AI application to provide real-time scanning and security of inputs and outputs based on the policies and rules in place,” Privacera’s Ganesan told Metaverse Post.

The integration with Amazon Bedrock expands Privacera’s existing integrations, making it a unified data security governance solution for over 20 AWS services, ranging from data and analytics services to third-party services running on AWS.

Last month, Privacera announced the General Availability of Privacera AI Governance (PAIG), one of the industry’s first comprehensive AI data governance solutions.

“Generative AI is in its early stages of adoption and will continue to expand. However, data security and compliance with increasingly robust mandates around consumer data protection, bias, and other abuses are proving to be a major impediment to mainstream adoption inside enterprises,” Privacera’s Ganesan told Metaverse Post. “Providing robust and consistent security across all your generative AI apps and models will
become a major advantage for early adopters in their respective markets.”

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About The Author

Victor is a Managing Tech Editor/Writer at Metaverse Post and covers artificial intelligence, crypto, data science, metaverse and cybersecurity within the enterprise realm. He boasts half a decade of media and AI experience working at well-known media outlets such as VentureBeat, DatatechVibe and Analytics India Magazine. Being a Media Mentor at prestigious universities including the Oxford and USC and with a Master's degree in data science and analytics, Victor is deeply committed to staying abreast of emerging trends. He offers readers the latest and most insightful narratives from the Tech and Web3 landscape.

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Victor Dey
Victor Dey

Victor is a Managing Tech Editor/Writer at Metaverse Post and covers artificial intelligence, crypto, data science, metaverse and cybersecurity within the enterprise realm. He boasts half a decade of media and AI experience working at well-known media outlets such as VentureBeat, DatatechVibe and Analytics India Magazine. Being a Media Mentor at prestigious universities including the Oxford and USC and with a Master's degree in data science and analytics, Victor is deeply committed to staying abreast of emerging trends. He offers readers the latest and most insightful narratives from the Tech and Web3 landscape.

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