Source code for pyecsca.ec.mult.base

"""Provides (mostly abstract) base classes for scalar multipliers, enums used to specify their parameters
and actions used in them."""

from abc import ABC, abstractmethod
from copy import copy
from enum import Enum
from public import public
from typing import Mapping, Tuple, Optional, ClassVar, Set, Type

from ..context import ResultAction, Action
from ..formula import Formula
from ..params import DomainParameters
from ..point import Point


[docs] @public class ProcessingDirection(Enum): """Scalar processing direction.""" LTR = "Left-to-right" RTL = "Right-to-left"
[docs] @public class AccumulationOrder(Enum): """Accumulation order (makes a difference for the projective result).""" PeqPR = "P = P + R" PeqRP = "P = R + P"
[docs] @public class ScalarMultiplicationAction(ResultAction): """A scalar multiplication of a point on a curve by a scalar.""" point: Point scalar: int def __init__(self, point: Point, scalar: int): super().__init__() self.point = point self.scalar = scalar def __repr__(self): return f"{self.__class__.__name__}({self.point}, {self.scalar})"
[docs] @public class PrecomputationAction(Action): """A precomputation of a point in scalar multiplication.""" params: DomainParameters point: Point def __init__(self, params: DomainParameters, point: Point): super().__init__() self.params = params self.point = point def __repr__(self): return f"{self.__class__.__name__}({self.params}, {self.point})"
[docs] @public class ScalarMultiplier(ABC): """ A scalar multiplication algorithm. .. note:: The __init__ method of all concrete subclasses needs to have type annotations so that configuration enumeration works. :param short_circuit: Whether the use of formulas will be guarded by short-circuit on inputs of the point at infinity. :param formulas: Formulas this instance will use. """ requires: ClassVar[Set[Type]] # Type[Formula] but mypy has a false positive """The set of formula types that the multiplier requires.""" optionals: ClassVar[Set[Type]] # Type[Formula] but mypy has a false positive """The optional set of formula types that the multiplier can use.""" short_circuit: bool """Whether the formulas will short-circuit upon input of the point at infinity.""" formulas: Mapping[str, Formula] """All formulas the multiplier was initialized with.""" _params: DomainParameters _point: Point _initialized: bool = False def __init__(self, short_circuit: bool = True, **formulas: Optional[Formula]): if ( len( { formula.coordinate_model for formula in formulas.values() if formula is not None } ) != 1 ): raise ValueError("Formulas need to belong to the same coordinate model.") self.short_circuit = short_circuit self.formulas = {k: v for k, v in formulas.items() if v is not None} found_required = set() for formula in self.formulas.values(): for required in self.requires: if isinstance(formula, required): found_required.add(required) break else: for optional in self.optionals: if isinstance(formula, optional): break else: raise ValueError("Not required or optional formulas provided.") if found_required != self.requires: raise ValueError("Required formulas missing.") def _add(self, one: Point, other: Point) -> Point: if "add" not in self.formulas: raise NotImplementedError if self.short_circuit: if one == self._params.curve.neutral: return copy(other) if other == self._params.curve.neutral: return copy(one) return self.formulas["add"]( self._params.curve.prime, one, other, **self._params.curve.parameters )[0] def _dbl(self, point: Point) -> Point: if "dbl" not in self.formulas: raise NotImplementedError if ( self.short_circuit and point == self._params.curve.neutral ): return copy(point) return self.formulas["dbl"]( self._params.curve.prime, point, **self._params.curve.parameters )[0] def _scl(self, point: Point) -> Point: if "scl" not in self.formulas: raise NotImplementedError return self.formulas["scl"]( self._params.curve.prime, point, **self._params.curve.parameters )[0] def _ladd(self, start: Point, to_dbl: Point, to_add: Point) -> Tuple[Point, ...]: if "ladd" not in self.formulas: raise NotImplementedError if self.short_circuit: if to_dbl == self._params.curve.neutral: return to_dbl, to_add if to_add == self._params.curve.neutral: return self._dbl(to_dbl), to_dbl return self.formulas["ladd"]( self._params.curve.prime, start, to_dbl, to_add, **self._params.curve.parameters, ) def _dadd(self, start: Point, one: Point, other: Point) -> Point: if "dadd" not in self.formulas: raise NotImplementedError if self.short_circuit: if one == self._params.curve.neutral: return copy(other) if other == self._params.curve.neutral: return copy(one) return self.formulas["dadd"]( self._params.curve.prime, start, one, other, **self._params.curve.parameters )[0] def _neg(self, point: Point) -> Point: if "neg" not in self.formulas: raise NotImplementedError return self.formulas["neg"]( self._params.curve.prime, point, **self._params.curve.parameters )[0] def __hash__(self): return hash((ScalarMultiplier, tuple(self.formulas.keys()), tuple(self.formulas.values()), self.short_circuit)) def __eq__(self, other): if not isinstance(other, ScalarMultiplier): return False return self.formulas == other.formulas and self.short_circuit == other.short_circuit def __repr__(self): return f"{self.__class__.__name__}({', '.join(map(str, self.formulas.values()))}, short_circuit={self.short_circuit})"
[docs] def init(self, params: DomainParameters, point: Point): """ Initialize the scalar multiplier with :paramref:`~.init.params` and a :paramref:`~.init.point`. .. warning:: The point is not verified to be on the curve represented in the domain parameters. :param params: The domain parameters to initialize the multiplier with. :param point: The point to initialize the multiplier with. """ coord_model = set(self.formulas.values()).pop().coordinate_model if ( params.curve.coordinate_model != coord_model or point.coordinate_model != coord_model ): raise ValueError self._params = params self._point = point self._initialized = True
[docs] @abstractmethod def multiply(self, scalar: int) -> Point: """ Multiply the point with the scalar. .. note:: The multiplier needs to be initialized by a call to the :py:meth:`.init` method. :param scalar: The scalar to use. :return: The resulting multiple. """ raise NotImplementedError
[docs] @public class AccumulatorMultiplier(ScalarMultiplier, ABC): """ A scalar multiplication algorithm mix-in class for a multiplier that accumulates. :param accumulation_order: The order of accumulation of points. """ accumulation_order: AccumulationOrder """The order of accumulation of points.""" def __init__(self, *args, accumulation_order: AccumulationOrder = AccumulationOrder.PeqPR, **kwargs): super().__init__(*args, **kwargs) self.accumulation_order = accumulation_order def _accumulate(self, p: Point, r: Point) -> Point: if self.accumulation_order is AccumulationOrder.PeqPR: p = self._add(p, r) elif self.accumulation_order is AccumulationOrder.PeqRP: p = self._add(r, p) return p