Sandboxed Generative AI Models With Memory-Range Isolation
Find Innovative SolutionsGenerate Solutions
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 privacy protections.
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 hardware isolation to prevent unauthorized access and maintain privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If generative AI models process sensitive data without isolation, then data processing capability is improved, but security and privacy are compromised
Solution Approach 1:
The system divides the data processing environment into separate sandboxes, each isolated from others. Generative AI models execute within these segmented environments, allowing data processing capability while preventing unauthorized access between sandboxes. The segmentation creates logical boundaries that maintain security while enabling productive processing.
Solution Approach 2:
The patent introduces an intermediary layer (the sandbox infrastructure with policy enforcement mechanisms) between the generative AI models and the sensitive data. This intermediary controls and mediates all data access requests, enabling processing while maintaining security through controlled interaction rather than direct access.
2Reliability
If generative AI models are isolated in sandbox environments, then security and privacy are improved, but system complexity increases
Solution Approach 1:
The sandbox infrastructure serves multiple functions simultaneously: it provides isolation for security, enables controlled data access for processing, enforces policies, and manages model execution. This multi-functionality reduces the need for separate complex systems for each function, thereby managing overall system complexity while maintaining security.
Solution Approach 2:
The system changes the operational parameters of the generative AI models by constraining them to specific execution environments with defined access rules. Rather than creating entirely new complex systems, the patent modifies the execution parameters and environmental constraints to achieve security without proportionally increasing complexity.
3Reliability
If strict policy enforcement is implemented in sandbox environments, then unauthorized access is prevented, but data sharing efficiency decreases
Solution Approach 1:
The policy enforcement mechanisms are designed to be dynamic rather than static. The system adaptively evaluates data sharing requests against policies in real-time, allowing legitimate efficient sharing while blocking unauthorized access. This dynamic approach optimizes the balance between security and efficiency by making access decisions based on current context rather than rigid rules.
Solution Approach 2:
The sandbox system implements feedback mechanisms where policy enforcement decisions are continuously evaluated and adjusted. The system learns from access patterns and policy outcomes, refining its enforcement strategies to maintain security while improving data sharing efficiency over time through iterative optimization.
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.