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Description:

tno.mpc.encryptionschemes.templates 4.1.2

TNO MPC Lab - Encryption Schemes - Templates
The TNO MPC lab consists of generic software components, procedures, and
functionalities developed and maintained on a regular basis to facilitate and
aid in the development of MPC solutions. The lab is a cross-project initiative
allowing us to integrate and reuse previously developed MPC functionalities to
boost the development of new protocols and solutions.
The package tno.mpc.encryption_schemes.templates is part of the TNO Python
Toolbox.
Generic frameworks for encryption schemes. Currently includes support for:

Generic encryption scheme (encryption_scheme.py);
Asymmetric encryption scheme (asymmetric_encryption_scheme.py);
Symmetric encryption scheme (symmetric_encryption_scheme.py);
Support for precomputation of randomness (randomized_encryption_scheme.py).

Limitations in (end-)use: the content of this software package may solely be
used for applications that comply with international export control laws.
This implementation of cryptographic software has not been audited. Use at your
own risk.
Documentation
Documentation of the tno.mpc.encryption_schemes.templates package can be found
here.
Install
Easily install the tno.mpc.encryption_schemes.templates package using pip:
$ python -m pip install tno.mpc.encryption_schemes.templates

Note:
A significant performance improvement can be achieved by installing the GMPY2
library.
$ python -m pip install 'tno.mpc.encryption_schemes.templates[gmpy]'

If you wish to run the tests you can use:
$ python -m pip install 'tno.mpc.encryption_schemes.templates[tests]'

Generating prepared randomness for RandomizedEncryptionSchemes
In the encryption process, RandomizedEncryptionSchemes require a random
number. A typical encryption process generates a large random number, processes
it in a way that is specific for (the private key of) the encryption scheme, and
used the prepared random value to encrypt a plaintext message. A similarly
prepared random value is required to rerandomize a ciphertext. This process of
generating and preparing randomness consumes a lot of time and processing power.
Fortunately, the randomness depends only on the encryption scheme and not on the
message that is to be encrypted. This makes it possible to prepare randomness a
priori. Our library facilitates this process by the concept of "randomness
sources". Three specific sources are shipped with the library, but you may
define your own RandomnessSource by implementing the
tno.mpc.encryption_schemes.templates._randomness_manager.RandomnessSource
protocol. The default sources are:

ContextlessSource, which yields randomness from a source that does not need
to be opened or closed (e.g. a list, tuple, function-call, ...).
FileSource, which creates a thread to read a file, store the values in RAM
and yield values on request.
ProcessSource, which creates one or more processes that all perform function
calls to store a predefined number of return values in RAM and yield on
request.

A RandomizedEncryptionScheme is configured with a ContextlessSource that
calls its generating function. However, it is often more efficient to start
generating a known amount of randomness earlier in the program execution. For
this, one may call RandomizedEncryptionScheme.boot_generation which internally
initializes and starts a ProcessSource, or requests an existing source to
generate more randomness (see also below). Other sources can be configured
through RandomizedEncryptionScheme.register_randomness_source.
Storing randomness for later use
Naturally, a maximum speed-up during runtime of your main protocol is achieved
by generating random values a priori. This looks as follows. First, the
key-generating party generates a public-private keypair and shares the public
key with the other participants. Now, every player pregenerates the amount of
randomness needed for her part of the protocol and stores it in a file. For
example, this can be done overnight or during the weekend. When the main
protocol is executed, every player uses the same scheme (public key) as
communicated before, configures the scheme to use the pregenerated randomness
from file, and runs the main protocol without the need to generate randomness
for encryption at that time. A minimal example is provided below.
from itertools import count
from pathlib import Path

from tno.mpc.encryption_schemes.templates.random_sources import FileSource
from tno.mpc.encryption_schemes.templates.randomized_encryption_scheme import (
RandomizedEncryptionScheme,
)

counter = count()

class MyRandomizedEncryptionScheme(RandomizedEncryptionScheme):
@staticmethod
def _generate_randomness() -> int:
"""Dummy randomness generator + preprocessing."""
return next(counter)

# --- empty definitions for all abstract methods ---
@classmethod
def from_security_parameter(cls, *args, **kwargs):
pass

@classmethod
def generate_key_material(cls, *args, **kwargs):
pass

@classmethod
def id_from_arguments(cls, *args, **kwargs):
pass

def encode(self, plaintext):
pass

def decode(self, encoded_plaintext):
pass

def _unsafe_encrypt_raw(self, plaintext):
pass

def _decrypt_raw(self, ciphertext):
pass

def __eq__(self, *args, **kwargs):
pass

def pregenerate_randomness_in_weekend(amount: int, path: Path):
# Initialize scheme, usually with parameters
generating_scheme = MyRandomizedEncryptionScheme()
# Generate randomness with two processes
generating_scheme.boot_randomness_generation(amount, max_workers=2)
# Save randomness to comma-separated csv
with open(path, "w") as file:
for _ in range(amount):
file.write(f"{generating_scheme.get_randomness()},")
# Shut down scheme to gracefully close source
generating_scheme.shut_down()

def use_pregenerated_randomness(amount: int, path: Path):
# Initialize scheme WITH THE SAME PARAMETERS!
consuming_scheme = MyRandomizedEncryptionScheme()
# Configure file as randomness source
consuming_scheme.register_randomness_source(FileSource(path))
# Consume randomness from file
for _ in range(amount):
print(consuming_scheme.get_randomness())
# Shut down scheme to gracefully close source
consuming_scheme.shut_down()

if __name__ == "__main__":
AMOUNT = 24
FILE_PATH = Path("randomness.csv")

pregenerate_randomness_in_weekend(AMOUNT, FILE_PATH)
use_pregenerated_randomness(AMOUNT, FILE_PATH)
# result (possibly not in this order): 0 0 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11