# NOVA for Healthcare: Verifiable Federated Learning Datasets

Phala's TEEs ensure confidential training, but lack persistent storage. NOVA complements TEEs by providing secure vaults for datasets pre/post-TEE, with revokable group membership. This enables verifiable, multi-party workflows: upload shared data, TEE fine-tunes, store models back—auditable via on-chain metadata.

* Uses off-chain TEE keys (Shade/Phala); no on-chain exposure.
* `getGroupKey` now auto-handles token claim/checksum verify.
* Update .env: CONTRACT\_ID=nova-sdk-5.testnet, SHADE\_API\_URL=...
* Run: Ensure group 'tee\_demo\_healthcare' exists in v2 contract.

## Use Case

In healthcare (e.g., Phala's success story: <https://phala.com/success-stories/healthcare-research>), hospitals share encrypted records for federated learning without exposure.

In the following demo, Hospital A uploads encrypted data to NOVA, Hospital B retrieves and process the data through Phala's TEE, it uploads the output data to NOVA. Hospital A retrieves Hospital B's output data, process it, and uploads the final output to NOVA.

## How NOVA Complements Phala's TEEs

Phala focuses on runtime privacy ("no storage, no logs"); NOVA adds decentralized persistence: encrypt/upload via composite\_upload, retrieve into TEE, output back. Focus: Data pipeline security without reinventing Phala's compute. NOVA handles pre-enclave sourcing (group auth) and post-enclave auditing (on-chain hashes/CIDs), extending Phala's quotes for full-lifecycle verifiability.

## Running the Demos

* Set .env (NEAR\_PRIVATE\_KEY, etc.).
* Rust: `cargo run --bin tee_federated_learning`.
* JS: `ts-node demos/tee_federated_learning.ts`.

Expected output:

```
Primary Account ID (Hospital A): <hospital_A.testnet>
Secondary Account ID (Hospital B): <hospital_B.testnet>
Hospital A uploaded to NOVA: CID QmW9oCqbrdMF8cKuYd14cwT3SszMWXRnaJ4aTZXKG4b1QA
Waiting for IPFS pin to propagate...
Hospital B output stored: CID QmSxuYEMhJpCm2wxC9zRQrbvaJN2irGtNdENCxRzs6J39C
Waiting for IPFS pin to propagate...
Hospital A final output stored: CID QmP5TiZYHByf1DDtXxVe5KjHj8r5Sp2E2MzLCMAxfH3Job
```


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