Intel corporation (20240330466). METHODS AND APPARATUS TO VERIFY THE INTEGRITY OF A MODEL simplified abstract
Contents
METHODS AND APPARATUS TO VERIFY THE INTEGRITY OF A MODEL
Organization Name
Inventor(s)
Scott Douglas Constable of Portland OR (US)
Marcin Andrzej Chrapek of Zurich (CH)
Marcin Spoczynski of Hillsboro OR (US)
Cory Cornelius of Portland OR (US)
Anjo Lucas Vahldiek-oberwagner of Berlin (DE)
METHODS AND APPARATUS TO VERIFY THE INTEGRITY OF A MODEL - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240330466 titled 'METHODS AND APPARATUS TO VERIFY THE INTEGRITY OF A MODEL
The patent application describes methods, apparatus, systems, and articles of manufacture for verifying the integrity of a model.
- Programmable circuitry is used to initialize a trusted execution environment, upload a security manifest and a machine learning model, determine storage based on the security manifest, validate the model, and output the validation result.
Key Features and Innovation:
- Use of programmable circuitry to establish a trusted execution environment.
- Uploading a security manifest and a machine learning model for verification.
- Determining storage of the model based on the security manifest.
- Validating the machine learning model to ensure its integrity.
Potential Applications: This technology can be applied in various industries such as cybersecurity, artificial intelligence, data analytics, and machine learning.
Problems Solved: This technology addresses the need for verifying the integrity of machine learning models to prevent malicious tampering or errors.
Benefits:
- Ensures the trustworthiness and reliability of machine learning models.
- Enhances security measures in data processing and analysis.
- Helps in maintaining the accuracy of predictive models.
Commercial Applications: This technology can be utilized by cybersecurity firms, data analytics companies, AI developers, and organizations dealing with sensitive data to ensure the integrity of their machine learning models.
Prior Art: Readers can explore prior art related to trusted execution environments, machine learning model validation, and security manifest uploading in the field of cybersecurity and artificial intelligence.
Frequently Updated Research: Stay updated on the latest advancements in trusted execution environments, machine learning model verification, and security manifest protocols to enhance the effectiveness of this technology.
Questions about the Technology: 1. How does the programmable circuitry ensure the initialization of a trusted execution environment? 2. What are the key factors considered in determining the validity of a machine learning model based on the security manifest?
Original Abstract Submitted
methods, apparatus, systems, and articles of manufacture to verify integrity of a model are disclosed. an example apparatus includes programmable circuitry to initialize an instance of a trusted execution environment; upload a security manifest of the trusted execution environment and a machine learning model; determine whether to store the machine learning model into a memory based on checking of the security manifest; determine whether the machine learning model is valid; and output a validation result.
