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2.4
2.4
  • What is Concrete?
  • Getting Started
    • Basics of FHE programs
    • Installation
    • Quick Start
    • Compatibility
    • Exactness
    • Performance
    • Terminology and Structure
  • Tutorials
    • Decorator
    • Progressbar
    • Formatting
    • Tagging
    • Extensions
    • Comparisons
    • Bitwise Operations
    • Table Lookups
    • Rounding
    • Floating Points
    • Multi Precision
    • Multi Parameters
    • Simulation
    • Direct Circuits
    • Statistics
    • Common Workarounds
  • Application Tutorials
    • Key Value Database
    • SHA-256
  • How To
    • Configure
    • Manage Keys
    • Deploy
    • Reuse Arguments
    • Debug
    • Call FHE circuits from other languages
  • Explanations
    • Frontend fusing
    • Compilation
      • Automatic Crypto Parameters choice
      • MLIR FHE Dialects
        • FHELinalg Dialect
        • FHE Dialect
        • TFHE Dialect
        • Concrete Dialect
        • Tracing Dialect
        • Runtime Dialect
        • SDFG Dialect
    • Security curves
  • Developer
    • Contribute
    • Project layout
    • Compiler backend
      • Adding a new backend
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On this page
  • Development of the circuit
  • Setting up a server
  • Setting up clients
  • Generating keys (on the client)
  • Encrypting inputs (on the client)
  • Performing computation (on the server)
  • Decrypting the result (on the client)

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  1. How To

Deploy

After developing your circuit, you may want to deploy it. However, sharing the details of your circuit with every client might not be desirable. As well as this, you might want to perform the computation on dedicated servers. In this case, you can use the Client and Server features of Concrete.

Development of the circuit

You can develop your circuit using the techniques discussed in previous chapters. Here is a simple example:

from concrete import fhe

@fhe.compiler({"x": "encrypted"})
def function(x):
    return x + 42

inputset = range(10)
circuit = function.compile(inputset)

Once you have your circuit, you can save everything the server needs:

circuit.server.save("server.zip")

Then, send server.zip to your computation server.

Setting up a server

You can load the server.zip you get from the development machine:

from concrete import fhe

server = fhe.Server.load("server.zip")

You will need to wait for requests from clients. The first likely request is for ClientSpecs.

Clients need ClientSpecs to generate keys and request computation. You can serialize ClientSpecs:

serialized_client_specs: str = server.client_specs.serialize()

Then, you can send it to the clients requesting it.

Setting up clients

After getting the serialized ClientSpecs from a server, you can create the client object:

client_specs = fhe.ClientSpecs.deserialize(serialized_client_specs)
client = fhe.Client(client_specs)

Generating keys (on the client)

Once you have the Client object, you can perform key generation:

client.keys.generate()

This method generates encryption/decryption keys and evaluation keys.

The server needs access to the evaluation keys that were just generated. You can serialize your evaluation keys as shown:

serialized_evaluation_keys: bytes = client.evaluation_keys.serialize()

After serialization, send the evaluation keys to the server.

Serialized evaluation keys are very large, so you may want to cache them on the server instead of sending them with each request.

Encrypting inputs (on the client)

The next step is to encrypt your inputs and request the server to perform some computation. This can be done in the following way:

arg: fhe.Value = client.encrypt(7)
serialized_arg: bytes = arg.serialize()

Then, send the serialized arguments to the server.

Performing computation (on the server)

Once you have serialized evaluation keys and serialized arguments, you can deserialize them:

deserialized_evaluation_keys = fhe.EvaluationKeys.deserialize(serialized_evaluation_keys)
deserialized_arg = fhe.Value.deserialize(serialized_arg)

You can perform the computation, as well:

result: fhe.Value = server.run(deserialized_arg, evaluation_keys=deserialized_evaluation_keys)
serialized_result: bytes = result.serialize()

Then, send the serialized result back to the client. After this, the client can decrypt to receive the result of the computation.

Decrypting the result (on the client)

Once you have received the serialized result of the computation from the server, you can deserialize it:

deserialized_result = fhe.Value.deserialize(serialized_result)

Then, decrypt the result:

decrypted_result = client.decrypt(deserialized_result)
assert decrypted_result == 49
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Last updated 1 year ago

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