Loading patent…
OwnerYuxin Ruan, Michael D. Doyle +1inventors
InventorsYuxin Ruan, Michael D. Doyle, Paul F. Doyle
Estimating the term…
The present invention provides a computer system and method for ensuring the architectural integrity and authenticity of neural networks using cryptographic techniques and timestamping mechanisms. The system certifies and validates the internal state of tensor and graph data structures within neural networks by computing hash values of the network's tensors and graphs and associating these values with specific time intervals. This can be achieved through use of transient-key cryptography, wherein a time-specific cryptographic key pair is generated for each interval, allowing the signing of hash values and ensuring data integrity. A timestamping authority issues timestamp tokens for the hash values, which are stored in a distributed, redundant archive for future verification. The validation process involves comparing the current state of the neural network with the stored hash values, ensuring any tampering or unauthorized modifications can be detected. This approach enhances the security and trustworthiness of neural network models across critical applications by safeguarding against adversarial attacks and model poisoning.
A computing system for generating a timestamped integrity record for a neural network model, the computing system comprising:
A computer-implemented method for generating a model timestamp for a neural network model, the method comprising:
A time-stamping authority system that uses transient-key cryptography, the time-stamping authority system comprising:
Dependencies are inferred from the claim text.