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import multiprocessing
import inspect
import tempfile
import sys
import os
from datetime import timedelta
from contextlib import contextmanager
from dataclasses import dataclass
from functools import partial, cached_property
from importlib import import_module, invalidate_caches
from pathlib import Path
from typing import Type, Any, Optional
from enum import Enum
from pyecsca.ec.params import DomainParameters, get_params
from pyecsca.ec.mult import *
from pyecsca.ec.countermeasures import GroupScalarRandomization, AdditiveSplitting, MultiplicativeSplitting, EuclideanSplitting
spawn_context = multiprocessing.get_context("spawn")
# Allow to use "spawn" multiprocessing method for function defined in a Jupyter notebook.
# https://neuromancer.sk/article/35
@contextmanager
def enable_spawn(func):
invalidate_caches()
source = inspect.getsource(func)
current_file_path = os.path.abspath(__file__)
with open(current_file_path, 'r') as self, tempfile.NamedTemporaryFile(suffix=".py", mode="w") as f:
f.write(self.read())
f.write(source)
f.flush()
path = Path(f.name)
directory = str(path.parent)
sys.path.append(directory)
module = import_module(str(path.stem))
yield getattr(module, func.__name__)
sys.path.remove(directory)
@dataclass(frozen=True)
class MultIdent:
klass: Type[ScalarMultiplier]
args: list[Any]
kwargs: dict[str, Any]
countermeasure: Optional[str] = None
def __init__(self, klass: Type[ScalarMultiplier], *args, **kwargs):
object.__setattr__(self, "klass", klass)
object.__setattr__(self, "args", args if args is not None else [])
if kwargs is not None and "countermeasure" in kwargs:
object.__setattr__(self, "countermeasure", kwargs["countermeasure"])
del kwargs["countermeasure"]
object.__setattr__(self, "kwargs", kwargs if kwargs is not None else {})
@cached_property
def partial(self):
func = partial(self.klass, *self.args, **self.kwargs)
if self.countermeasure is None:
return func
if self.countermeasure == "gsr":
return lambda *args, **kwargs: GroupScalarRandomization(func(*args, **kwargs))
elif self.countermeasure == "additive":
return lambda *args, **kwargs: AdditiveSplitting(func(*args, **kwargs))
elif self.countermeasure == "multiplicative":
return lambda *args, **kwargs: MultiplicativeSplitting(func(*args, **kwargs))
elif self.countermeasure == "euclidean":
return lambda *args, **kwargs: EuclideanSplitting(func(*args, **kwargs))
def with_countermeasure(self, countermeasure: str | None):
if countermeasure not in (None, "gsr", "additive", "multiplicative", "euclidean"):
raise ValueError(f"Unknown countermeasure: {countermeasure}")
return MultIdent(self.klass, *self.args, **self.kwargs, countermeasure=countermeasure)
def __str__(self):
args = ("_" + ",".join(list(map(str, self.args)))) if self.args else ""
kwargs = ("_" + ",".join(f"{str(k)}:{v.name if isinstance(v, Enum) else str(v)}" for k,v in self.kwargs.items())) if self.kwargs else ""
countermeasure = f"+{self.countermeasure}" if self.countermeasure is not None else ""
return f"{self.klass.__name__}{args}{kwargs}{countermeasure}"
def __repr__(self):
return str(self)
def __hash__(self):
return hash((self.klass, self.countermeasure, tuple(self.args), tuple(self.kwargs.keys()), tuple(self.kwargs.values())))
@dataclass
class MultResults:
multiplications: list[set[int]]
samples: int
duration: Optional[float] = None
kind: Optional[str] = None
def merge(self, other: "MultResults"):
self.multiplications.extend(other.multiplications)
self.samples += other.samples
def __len__(self):
return self.samples
def __iter__(self):
yield from self.multiplications
def __getitem__(self, i):
return self.multiplications[i]
def __str__(self):
duration = timedelta(seconds=int(self.duration)) if self.duration is not None else ""
kind = self.kind if self.kind is not None else ""
return f"MultResults({self.samples},{duration},{kind})"
def __repr__(self):
return str(self)
@dataclass
class ProbMap:
probs: dict[int, float]
samples: int
kind: Optional[str] = None
def __len__(self):
return len(self.probs)
def __iter__(self):
yield from self.probs
def __getitem__(self, i):
return self.probs[i]
def keys(self):
return self.probs.keys()
def values(self):
return self.probs.values()
def items(self):
return self.probs.items()
def narrow(self, divisors: set[int]):
self.probs = {k:v for k, v in self.probs.items() if k in divisors}
def merge(self, other: "ProbMap") -> None:
if self.kind != other.kind:
raise ValueError("Merging ProbMaps of different kinds leads to unexpected results.")
new_keys = set(self.keys()).union(other.keys())
result = {}
for key in new_keys:
if key in self and key in other:
result[key] = (self[key] * self.samples + other[key] * other.samples) / (self.samples + other.samples)
elif key in self:
result[key] = self[key]
elif key in other:
result[key] = other[key]
self.probs = result
self.samples += other.samples
def enrich(self, other: "ProbMap") -> None:
if self.samples != other.samples:
raise ValueError("Enriching can only work on equal amount of samples (same run, different divisors)")
if self.kind != other.kind:
raise ValueError("Enriching ProbMaps of different kinds leads to unexpected results.")
self.probs.update(other.probs)
# All dbl-and-add multipliers from https://github.com/J08nY/pyecsca/blob/master/pyecsca/ec/mult
window_mults = [
MultIdent(SlidingWindowMultiplier, width=3),
MultIdent(SlidingWindowMultiplier, width=4),
MultIdent(SlidingWindowMultiplier, width=5),
MultIdent(SlidingWindowMultiplier, width=6),
MultIdent(FixedWindowLTRMultiplier, m=2**4),
MultIdent(FixedWindowLTRMultiplier, m=2**5),
MultIdent(FixedWindowLTRMultiplier, m=2**6),
MultIdent(WindowBoothMultiplier, width=3),
MultIdent(WindowBoothMultiplier, width=4),
MultIdent(WindowBoothMultiplier, width=5),
MultIdent(WindowBoothMultiplier, width=6)
]
naf_mults = [
MultIdent(WindowNAFMultiplier, width=3),
MultIdent(WindowNAFMultiplier, width=4),
MultIdent(WindowNAFMultiplier, width=5),
MultIdent(WindowNAFMultiplier, width=6),
MultIdent(BinaryNAFMultiplier, direction=ProcessingDirection.LTR),
MultIdent(BinaryNAFMultiplier, direction=ProcessingDirection.RTL)
]
comb_mults = [
MultIdent(CombMultiplier, width=2),
MultIdent(CombMultiplier, width=3),
MultIdent(CombMultiplier, width=4),
MultIdent(CombMultiplier, width=5),
MultIdent(CombMultiplier, width=6),
MultIdent(BGMWMultiplier, width=2, direction=ProcessingDirection.LTR),
MultIdent(BGMWMultiplier, width=3, direction=ProcessingDirection.LTR),
MultIdent(BGMWMultiplier, width=4, direction=ProcessingDirection.LTR),
MultIdent(BGMWMultiplier, width=5, direction=ProcessingDirection.LTR),
MultIdent(BGMWMultiplier, width=6, direction=ProcessingDirection.LTR),
MultIdent(BGMWMultiplier, width=2, direction=ProcessingDirection.RTL),
MultIdent(BGMWMultiplier, width=3, direction=ProcessingDirection.RTL),
MultIdent(BGMWMultiplier, width=4, direction=ProcessingDirection.RTL),
MultIdent(BGMWMultiplier, width=5, direction=ProcessingDirection.RTL),
MultIdent(BGMWMultiplier, width=6, direction=ProcessingDirection.RTL)
]
binary_mults = [
MultIdent(LTRMultiplier, always=False),
MultIdent(LTRMultiplier, always=True),
MultIdent(RTLMultiplier, always=False),
MultIdent(RTLMultiplier, always=True),
MultIdent(CoronMultiplier)
]
other_mults = [
MultIdent(FullPrecompMultiplier, always=False),
MultIdent(FullPrecompMultiplier, always=True),
MultIdent(SimpleLadderMultiplier, complete=True),
MultIdent(SimpleLadderMultiplier, complete=False)
]
all_mults = window_mults + naf_mults + binary_mults + other_mults + comb_mults
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