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, total_ordering from importlib import import_module, invalidate_caches from pathlib import Path from typing import Type, Any, Optional from enum import Enum from statsmodels.stats.proportion import proportion_confint from pyecsca.ec.params import DomainParameters, get_params from pyecsca.ec.mult import * from pyecsca.ec.countermeasures import GroupScalarRandomization, AdditiveSplitting, MultiplicativeSplitting, EuclideanSplitting, BrumleyTuveri 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) @total_ordering 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)) elif self.countermeasure == "bt": return lambda *args, **kwargs: BrumleyTuveri(func(*args, **kwargs)) def with_countermeasure(self, countermeasure: str | None): if countermeasure not in (None, "gsr", "additive", "multiplicative", "euclidean", "bt"): raise ValueError(f"Unknown countermeasure: {countermeasure}") return MultIdent(self.klass, *self.args, **self.kwargs, countermeasure=countermeasure) def __str__(self): name = self.klass.__name__.replace("Multiplier", "") args = ("_" + ",".join(list(map(str, self.args)))) if self.args else "" kwmap = {"recoding_direction": "recode", "direction": "dir", "width": "w"} kwargs = ("_" + ",".join(f"{kwmap.get(k, 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"{name}{args}{kwargs}{countermeasure}" def __lt__(self, other): if not isinstance(other, MultIdent): return NotImplemented return str(self) < str(other) 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=2, recoding_direction=ProcessingDirection.LTR), MultIdent(SlidingWindowMultiplier, width=3, recoding_direction=ProcessingDirection.LTR), MultIdent(SlidingWindowMultiplier, width=4, recoding_direction=ProcessingDirection.LTR), MultIdent(SlidingWindowMultiplier, width=5, recoding_direction=ProcessingDirection.LTR), MultIdent(SlidingWindowMultiplier, width=6, recoding_direction=ProcessingDirection.LTR), MultIdent(SlidingWindowMultiplier, width=2, recoding_direction=ProcessingDirection.RTL), MultIdent(SlidingWindowMultiplier, width=3, recoding_direction=ProcessingDirection.RTL), MultIdent(SlidingWindowMultiplier, width=4, recoding_direction=ProcessingDirection.RTL), MultIdent(SlidingWindowMultiplier, width=5, recoding_direction=ProcessingDirection.RTL), MultIdent(SlidingWindowMultiplier, width=6, recoding_direction=ProcessingDirection.RTL), MultIdent(FixedWindowLTRMultiplier, m=2**1), MultIdent(FixedWindowLTRMultiplier, m=2**2), MultIdent(FixedWindowLTRMultiplier, m=2**3), MultIdent(FixedWindowLTRMultiplier, m=2**4), MultIdent(FixedWindowLTRMultiplier, m=2**5), MultIdent(FixedWindowLTRMultiplier, m=2**6), MultIdent(WindowBoothMultiplier, width=2), MultIdent(WindowBoothMultiplier, width=3), MultIdent(WindowBoothMultiplier, width=4), MultIdent(WindowBoothMultiplier, width=5), MultIdent(WindowBoothMultiplier, width=6) ] naf_mults = [ MultIdent(WindowNAFMultiplier, width=2), MultIdent(WindowNAFMultiplier, width=3), MultIdent(WindowNAFMultiplier, width=4), MultIdent(WindowNAFMultiplier, width=5), MultIdent(WindowNAFMultiplier, width=6), MultIdent(BinaryNAFMultiplier, always=False, direction=ProcessingDirection.LTR), MultIdent(BinaryNAFMultiplier, always=False, direction=ProcessingDirection.RTL), MultIdent(BinaryNAFMultiplier, always=True, direction=ProcessingDirection.LTR), MultIdent(BinaryNAFMultiplier, always=True, direction=ProcessingDirection.RTL) ] comb_mults = [ MultIdent(CombMultiplier, width=2, always=True), MultIdent(CombMultiplier, width=3, always=True), MultIdent(CombMultiplier, width=4, always=True), MultIdent(CombMultiplier, width=5, always=True), MultIdent(CombMultiplier, width=6, always=True), MultIdent(CombMultiplier, width=2, always=False), MultIdent(CombMultiplier, width=3, always=False), MultIdent(CombMultiplier, width=4, always=False), MultIdent(CombMultiplier, width=5, always=False), MultIdent(CombMultiplier, width=6, always=False), 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, complete=True), MultIdent(LTRMultiplier, always=True, complete=True), MultIdent(LTRMultiplier, always=False, complete=False), MultIdent(LTRMultiplier, always=True, complete=False), MultIdent(RTLMultiplier, always=False, complete=True), MultIdent(RTLMultiplier, always=True, complete=True), MultIdent(RTLMultiplier, always=False, complete=False), MultIdent(RTLMultiplier, always=True, complete=False), MultIdent(CoronMultiplier) ] other_mults = [ MultIdent(FullPrecompMultiplier, always=False, complete=True), MultIdent(FullPrecompMultiplier, always=True, complete=True), MultIdent(FullPrecompMultiplier, always=False, complete=False), MultIdent(FullPrecompMultiplier, always=True, complete=False), MultIdent(SimpleLadderMultiplier, complete=True), MultIdent(SimpleLadderMultiplier, complete=False) ] all_mults = window_mults + naf_mults + binary_mults + other_mults + comb_mults all_mults_with_ctr = [mult.with_countermeasure(ctr) for mult in all_mults for ctr in (None, "gsr", "additive", "multiplicative", "euclidean", "bt")] def powers_of(k, max_power=20): return [k**i for i in range(1, max_power)] def prod_combine(one, other): return [a * b for a, b in itertools.product(one, other)] small_primes = [3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97, 101, 103, 107, 109, 113, 127, 131, 137, 139, 149, 151, 157, 163, 167, 173, 179, 181, 191, 193, 197, 199] medium_primes = [211, 223, 227, 229, 233, 239, 241, 251, 257, 263, 269, 271, 277, 281, 283, 293, 307, 311, 313, 317, 331, 337, 347, 349, 353, 359, 367, 373, 379, 383, 389, 397] large_primes = [401, 409, 419, 421, 431, 433, 439, 443, 449, 457, 461, 463, 467, 479, 487, 491, 499, 503, 509, 521, 523, 541, 547, 557, 563, 569, 571, 577, 587, 593, 599, 601, 607, 613, 617, 619, 631, 641, 643, 647, 653, 659, 661, 673, 677, 683, 691, 701, 709, 719, 727, 733, 739, 743, 751, 757, 761, 769, 773, 787, 797, 809, 811, 821, 823, 827, 829, 839, 853, 857, 859, 863, 877, 881, 883, 887, 907, 911, 919, 929, 937, 941, 947, 953, 967, 971, 977, 983, 991, 997] all_integers = list(range(1, 400)) all_even = list(range(2, 400, 2)) all_odd = list(range(1, 400, 2)) all_primes = small_primes + medium_primes + large_primes divisor_map = { "small_primes": small_primes, "medium_primes": medium_primes, "large_primes": large_primes, "all_primes": all_primes, "all_integers": all_integers, "all_even": all_even, "all_odd": all_odd, "powers_of_2": powers_of(2), "powers_of_2_large": powers_of(2, 256), "powers_of_2_large_3": [i * 3 for i in powers_of(2, 256)], "powers_of_2_large_p1": [i + 1 for i in powers_of(2, 256)], "powers_of_2_large_m1": [i - 1 for i in powers_of(2, 256)], "powers_of_2_large_pmautobus": sorted(set([i + j for i in powers_of(2, 256) for j in range(-5,5) if i+j > 0])), "powers_of_3": powers_of(3), } divisor_map["all"] = list(sorted(set().union(*[v for v in divisor_map.values()]))) def conf_interval(p: float, samples: int, alpha: float = 0.05) -> tuple[float, float]: return proportion_confint(round(p*samples), samples, alpha, method="wilson")