F5 AI Data Protection and Governance

Real-time Data Protection and Governance for AI Applications

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Description

F5 AI Data Protection and Governance represents upcoming capabilities integrated into the F5 Application Delivery and Security Platform, designed to address the complex data security challenges presented by modern AI applications. As organizations increasingly leverage generative AI and other technologies, managing the massive amounts of data moving between stores, models, and applications becomes critical. Traditional tools often fail to provide the necessary real-time visibility, accurate classification, and robust enforcement needed to protect sensitive information and meet regulatory requirements, especially concerning large volumes of AI training data or user inputs.

Leveraging technology acquired from LeakSignal, these features will provide precise, real-time identification of data types and destinations, allowing for effective policy-driven risk management. Organizations will gain enhanced observability to not only monitor but also control data flow, enabling swift action when necessary. Continuous monitoring and auditing capabilities aim to ensure ongoing compliance with data privacy standards, offering organizations the confidence to innovate with AI without compromising security or governance across their application ecosystem, including APIs, endpoints, and LLM interactions.

Key Features

Real-time data classification and analysis: Precisely identifies the type of data being transmitted and its destination.
Policy-driven enforcement and incident response: Enables control over data flow based on defined policies and facilitates action when needed.
Continuous monitoring and governance: Provides ongoing auditing and monitoring of data access and transmission for compliance.
AI Data Mediation: Mediates data input and output for large language models (LLMs).
Broad Protection Scope: Protects sensitive data in APIs, traditional and AI applications, and at endpoints.

Use Cases

Securing sensitive data used in AI model training.
Governing user inputs provided to generative AI models.
Ensuring AI application compliance with data privacy regulations (e.g., GDPR, CCPA).
Protecting proprietary data within APIs consumed by AI systems.
Preventing data leakage in real-time across distributed applications.
Mediating and securing data interactions with Large Language Models (LLMs).