/Patent Tracker
MicrosoftPatent applicationAI & softwareInterest 6/10

Microsoft patents method to split AI models for hardware security

Patent drawing
Patent drawing from the official filing.

Microsoft describes a system that breaks an AI model into smaller sections, or partitions, based on how sensitive the data is at each stage. The system then assigns each section to a specific hardware component that has the right level of physical or software protection to keep that data safe.

Why it mattersThis approach could help companies run AI models on standard hardware while ensuring that sensitive user data is only processed on chips with the necessary security protections.

In the filing’s own words

A data processing system implements a model partitioning framework that partitions the layers of a neural network of an AI model into multiple partitions. Each partition includes a subset of the layers of the neural network architecture and each partition has different security requirements based on whether the layers in the partition are receiving sensitive input data or operating on data from which features of the sensitive input data can be reconstructed. The model partitioning framework determines the security requirements of each of the layers of the neural network architecture and partitioning the neural network architecture into multiple partitions based on the security requirements of the layers included in each partition and the security features of the hardware security domains available for operating each of the partitions. Each partition is operated in a hardware security domain that satisfies the security requirements of that respective partition.

What exactly they claim (claim 1)

1. A data processing system comprising: a processor; and a memory storing executable instructions that, when executed, cause the processor alone or in combination with other processors to perform operations of: analyzing program code representing a neural network architecture of an artificial intelligence model to generate a map of layers of the neural network architecture by identifying connections between layers of the neural network architecture and inspecting a flow of information between the layers of the artificial intelligence model, the map including connectivity information representing the connections between the layers of the neural network architecture that facilitate information flowing between the layers, and dependency information representing relationships between layers in which an output of one layer is provided as an input to another layer; obtaining hardware information indicating computing hardware components available for operating portions of the artificial intelligence model, the computing hardware components being associated with one of a plurality of hardware security domains providing security features for protecting sensitive data being processed by the computing hardware components from unauthorized access, the security features comprising physical components, software, or a combination thereof that prevent unauthorized access or tampering with the sensitive data; determining security requirements for each of the layers of the neural network architecture based on the map of the layers of the neural network architecture by analyzing the map to determine a position of each of the layers relative to an input layer of the neural network architecture and a layer type associated with each of the layers; determining which hardware components can satisfy the security requirements for each of the layers of the neural network architecture; partitioning the neural network architecture into a partitioned neural network architecture that includes partitions comprising one or more layers of the neural network architecture based on the security requirements of each of the layers to be operated on selected hardware components from among the computing hardware components, the selected hardware components satisfy the security requirements of the layers included in a respective partition; and operating the partitioned neural network architecture on the selected hardware components.

Facts

Company
Microsoft (Microsoft Technology Licensing, LLC)
Official title
DYNAMIC HARDWARE AWARE MODEL PARTITIONING
Publication number
US20260300489A1
Application number
19089629
Filed
Mar 25, 2025
Published
Oct 1, 2026
Inventors
1
Claims
20

Classified under

G06F 21/57 Physics & computingG06N 3/105 Physics & computingG06F 2221/034 Physics & computing

More from Microsoft in AI & software

Summaries are simplified from the filing’s own abstract and first claim. A patent filing is not a product announcement.
Patent data and drawings: U.S. Patent and Trademark Office (USPTO). Nebula is not affiliated with or endorsed by the USPTO.