Sandboxed Generative AI Model Isolation for Secure Data Vaults
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Solution Overview
Problem
Existing generative AI models lack adequate security and privacy measures, particularly when used in augmented and virtual reality environments, as they often process sensitive data without sufficient isolation and control over user data.
Innovation Solution
A secure data vault system is implemented within the operating system to isolate generative AI models, ensuring that raw data from devices like cameras and microphones is processed within a sandbox environment, with strict policy enforcement and secure data management to enhance privacy and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If generative AI models process raw data from cameras and microphones without isolation, then processing capability and user experience are improved, but security vulnerabilities and privacy risks increase
Solution Approach 1:
The system divides the data processing architecture into distinct segments: a secure data vault for storing sensitive raw data, a sandboxed execution environment for running AI models, and controlled data transfer interfaces. This segmentation isolates the AI model processing from direct access to sensitive data, maintaining security while enabling processing capabilities.
Solution Approach 2:
The patent introduces an intermediary secure data vault system that mediates between the AI models and raw data sources. The vault acts as a controlled interface, allowing AI models to process data through enforced security policies without direct exposure to sensitive information, thus resolving the contradiction between processing capability and security.
2Productivity
If generative AI models have direct access to user data, then data processing efficiency is improved, but user privacy and data security are compromised
Solution Approach 1:
The architecture segments data access into controlled portions through the secure data vault. The AI models receive only the data portions necessary for their function through enforced policies, rather than having direct access to all user data. This segmentation maintains processing efficiency while minimizing privacy exposure.
Solution Approach 2:
The sandboxed execution environment creates an inert or controlled atmosphere for AI model operation. Within this isolated environment, models can process data efficiently without the risk of compromising user privacy, as the environment itself enforces security boundaries and policy restrictions.
3Reliability
If a secure sandbox environment is implemented for AI models, then security and privacy are improved, but system complexity increases
Solution Approach 1:
The patent merges the secure data vault, sandboxed execution environment, and policy enforcement mechanisms into an integrated system. By combining these security components into a unified architecture, the system reduces overall complexity compared to implementing separate security layers, while still providing comprehensive protection for AI model processing.
Data Source
AI summary
A generative artificial intelligence (AI) system includes a generative AI model configured to generate outputs based on a training data set. The AI system additionally includes a secure data vault system. The secure data vault system additionally includes a sandbox system storing the generative AI model and operatively coupled to the generative AI model to send inputs to generate the outputs from the generative AI model, wherein the sandbox system comprises an execution environment configured to restrict execution of the generative AI model to a predefined memory address range. The secure data vault system further includes a secure network service communicatively coupled to the sandbox system and configured to authenticate a connection to an external system and to download from the external system an update package for the generative AI model when the connection is authenticated.