How-To: Decrypt Output Data

After receiving the encrypted output from a query request, the end-user must decrypt the message using their Secret Key. This guide explains how to perform the decryption process.

Prerequisites

Encrypted Output: The output must be retrieved from a successful query execution.
Secret Key: The user’s Secret Key is required to decrypt the message.

Use the following code snippet to decrypt the output data. Provide the User Access Token and the encrypted output message 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)

serialized_ct_res = agent_app.user.apply_hom_pipeline(serialized_ct)

serialized_pt = agent_app.user.decrypt(serialized_ct_res)

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);

// Send your encrypted query to and get a resopnse
const ct_res = await latticaClient.apply_query(ct);

// Decrypt your query result
const pt_res = await latticaClient.decrypt(ct_res);

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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) serialized_ct_res = agent_app.user.apply_hom_pipeline(serialized_ct) serialized_pt = agent_app.user.decrypt(serialized_ct_res)

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); // Send your encrypted query to and get a resopnse const ct_res = await latticaClient.apply_query(ct); // Decrypt your query result const pt_res = await latticaClient.decrypt(ct_res);