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improved CPU profiling and added cli utility to calc rounds for given seconds

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This commit is contained in:
Kevin Froman 2020-03-18 19:50:34 -05:00
parent fe06c759cb
commit 26bad82e06
2 changed files with 24 additions and 4 deletions
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8
README.md
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@ -2,9 +2,15 @@
<p align="center"><i>Simple <a href="https://eprint.iacr.org/2018/601.pdf">Verifiable Delay Function<a> using <a href="https://eprint.iacr.org/2016/492.pdf">MiMC</a></i></p> <p align="center"><i>Simple <a href="https://eprint.iacr.org/2018/601.pdf">Verifiable Delay Function<a> using <a href="https://eprint.iacr.org/2016/492.pdf">MiMC</a></i></p>
## Applications
This module was created for use in reducing spam in a similar manner to [HashCash](https://en.wikipedia.org/wiki/Hashcash). However, some potential uses for VDFs include blockchains and verifiable lotteries.
## Security ## Security
This code has not been audited for security. It is not currently recommended for protecting against anything but denial of service, even though MiMC is able to do much more. This code has not been audited for security. It is not currently recommended for protecting against anything but denial of service, even though MiMC is able to do much more. If used, make sure it is not protecting anything critical.
In addition, since this is a Python implementation, attackers can be faster than typical users of an application by using faster language implementations or even FPGAs.

20
mimcvdf/__init__.py
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"""High level Verifiable Delay Function using keccak (sha3).""" """High level Verifiable Delay Function using keccak (sha3)."""
from hashlib import sha3_256 from hashlib import sha3_256
from typing import Union from typing import Union
import timeit import time
from statistics import mean
from math import ceil
from .mimc import forward_mimc, reverse_mimc from .mimc import forward_mimc, reverse_mimc
""" """
@ -45,5 +47,17 @@ def vdf_verify(
hex(reverse_mimc(int(test_hash, 16), rounds)).replace('0x', '') hex(reverse_mimc(int(test_hash, 16), rounds)).replace('0x', '')
def profile_cpu_speed(rounds=1000) -> float: def profile_cpu_speed(rounds=1000, seconds=1) -> float:
return timeit.timeit(lambda: vdf_create(b"test", rounds), number=100) time_results = []
for _ in range(10000):
start = time.time()
vdf_create(b"t", rounds)
end = time.time()
time_results.append(end - start)
return (seconds / mean(time_results) * 1000)
if __name__ == "__main__":
print("Calculate how may rounds are needed for X seconds (influenced by system processes): ")
seconds = int(input("Seconds: "))
print("Rounds:", ceil(profile_cpu_speed()))