How-To: Encrypt Input Message

Prerequisites

Encryption Keys:
- A Secret Key must be defined in the Query Client to encrypt and decrypt messages.
- The corresponding Evaluation Key must be deployed in LatticaAI.
If the key pair is already defined, you do not need to create it again.
User Access Token:
- The user must have a valid Access Token, which provides permission to interact with the AI model.
- Tokens are unique to each user and model.

Use the following code snippet to encrypt the input message. The encryption process takes the User Access Token and the message to be encrypted as parameters:

import lattica_common.app_api as agent_app

# Notice your query token expires in 30 days
query_token = "the_query_token_you_got_using_the_generate_user_token"

# user_data is a tuple of: 
# (serialized_context, serialized_secret_key, serialized_homseq)
# which you need for encrypting the query and querying the model
user_data = agent_app.user.query_offline_phase(query_token)

dataset = pd.read_csv('data/mnist_data.csv').values / 255
data = torch.tensor(dataset[0])
serialized_ct = agent_app.user.encrypt(user_data, dataset)

import { LatticaQueryClient } from 'lattica-query-client';

const client = new LatticaQueryClient('your-jwt-query-token');

// Uploaded the EK
const initialized = await client.init();
if (!initialized) {
  console.error('Initialization failed: The EK was not successfully uploaded.');
  throw new Error('EK upload failed.');
}
console.log('EK uploaded successfully.');

// The data you want to encrypt
const inputTensor = ....;

// Encrypt the provided input
const ct = await client.encrypt(pt);

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import lattica_common.app_api as agent_app # Notice your query token expires in 30 days query_token = "the_query_token_you_got_using_the_generate_user_token" # user_data is a tuple of: # (serialized_context, serialized_secret_key, serialized_homseq) # which you need for encrypting the query and querying the model user_data = agent_app.user.query_offline_phase(query_token) dataset = pd.read_csv('data/mnist_data.csv').values / 255 data = torch.tensor(dataset[0]) serialized_ct = agent_app.user.encrypt(user_data, dataset)

import { LatticaQueryClient } from 'lattica-query-client'; const client = new LatticaQueryClient('your-jwt-query-token'); // Uploaded the EK const initialized = await client.init(); if (!initialized) { console.error('Initialization failed: The EK was not successfully uploaded.'); throw new Error('EK upload failed.'); } console.log('EK uploaded successfully.'); // The data you want to encrypt const inputTensor = ....; // Encrypt the provided input const ct = await client.encrypt(pt);