Secure AI Model Hosting

OmniTensor’s decentralized infrastructure guarantees the security and isolation of AI models deployed by businesses. To ensure optimal protection and reliability, the following measures are applied:

Decentralized AI Model Hosting

Models are hosted across a distributed network of nodes, leveraging the Decentralized Physical Infrastructure Network (DePIN). This removes the risk of single points of failure and ensures the models remain available even during network disruptions.

• Fault Tolerance

  In the event of node failure, the model and its associated data are replicated across other nodes in the network, ensuring seamless operation without data loss or downtime.

• Geographic Distribution

  Models can be deployed across multiple geographic regions, complying with data sovereignty laws, ensuring that data processing occurs within authorized jurisdictions.

Private Model Hosting

Businesses can opt for private model hosting to restrict access to their AI models. OmniTensor provides private cloud setups where businesses can run sensitive AI computations isolated from the public network.

• Private Inference Requests - Models hosted privately can handle AI inference tasks without exposure to the public network, using encrypted channels to safeguard request and response data.

Example Terminal Command for Private Hosting:

omnitensor deploy --model <model_name> --private --region EU

Immutable Model Versioning

Every version of an AI model deployed on OmniTensor is recorded immutably on the blockchain. This ensures that businesses can audit and revert to any previous version if needed, maintaining full control over their AI deployments.

omnitensor model-history <model_name>
# Output: all versions with corresponding deployment hashes

AI Model Integrity Verification

To prevent tampering, OmniTensor uses cryptographic hash functions to verify the integrity of AI models before deployment. Each model’s hash is recorded on the blockchain, ensuring that any unauthorized modifications are instantly detectable.

# Integrity check for AI model deployment
model_hash = hashlib.sha256(model_file).hexdigest()
blockchain_record = omnitensor.get_model_hash(model_name)

assert model_hash == blockchain_record, "Model integrity compromised!"

Secure Model Updates and Patch Management

OmniTensor provides secure mechanisms for businesses to update their AI models. Using multi-signature approval, organizations can ensure that updates to their models are reviewed and authorized before deployment. This is critical for maintaining the security and performance of business-critical AI systems.