Edge AI Model Protection With Hardware-Bound Secure Elements
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Solution Overview
Problem
Existing AI models deployed on edge devices are vulnerable to manipulation and counterfeiting, lacking effective protection mechanisms.
Innovation Solution
Implementing a secure element or trusted execution environment on edge devices to store and manage a salt, which is used to modify and encrypt data before running AI models, ensuring only authorized devices can utilize the models effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If AI models are deployed directly on edge devices without protection mechanisms, then device complexity is reduced and ease of operation is improved, but security and reliability deteriorate due to vulnerability against manipulation and counterfeiting
Solution Approach 1:
A trusted execution environment (TEE) or secure element is introduced as an intermediary between the AI model and the edge device processor. This intermediary component handles cryptographic operations and protects the AI model parameters, allowing the model to be bound to specific hardware while maintaining ease of operation through automated security mechanisms
Solution Approach 2:
The patent replaces traditional software-based protection mechanisms with hardware-based trusted execution environments or secure elements. This substitution provides stronger security guarantees by leveraging hardware security features, effectively protecting against manipulation and counterfeiting while maintaining operational simplicity
2Reliability
If AI models are protected through binding to specific hardware using trusted execution environments, then security and reliability are improved, but device complexity increases
Solution Approach 1:
The trusted execution environment or secure element serves multiple functions: it protects AI model parameters, enables hardware binding, performs cryptographic operations, and provides authentication. By consolidating these functions into a single component, the patent improves security without proportionally increasing overall device complexity
Solution Approach 2:
The trusted execution environment operates autonomously to protect AI models, automatically handling cryptographic operations and hardware binding without requiring complex user intervention or additional software layers. This self-service approach simplifies the overall system architecture while maintaining strong security
Data Source
AI summary
An edge device is proposed that comprises a first memory configured to receive and store an artificial intelligence model (AI model) and a pre-processor configured to pre-process sensor data. The edge device further comprises a protected memory for storing modifying data, and a classification stage for running the AI model on the pre-processed data that is modified based on the modifying data. The classification stage outputs output data generated by running the AI model on the modified pre-processed data.