Milp cipher model

class MilpCipherModel(cipher, n_window_heuristic=None)

Bases: MilpModel

property binary_variable
build_cipher_model(fixed_variables=[])

Build the cipher model.

Cannot be done with MILP, non-linear components cannot be modeled with only inequalities.

INPUT:

  • fixed_variables – list (default: []); dictionaries containing the variables to be fixed in standard format

See also

set_fixed_variables()

EXAMPLES:

sage: from claasp.cipher_modules.models.milp.milp_models.milp_cipher_model import MilpCipherModel
sage: from claasp.ciphers.block_ciphers.speck_block_cipher import SpeckBlockCipher
sage: speck = SpeckBlockCipher(number_of_rounds=22)
sage: milp = MilpCipherModel(speck)
sage: milp.init_model_in_sage_milp_class()
sage: milp.build_cipher_model()
...
property cipher
property cipher_id
fix_variables_value_constraints(fixed_variables=[])

Return a list of constraints that fix the input variables to a specific value.

INPUT:

  • fixed_variables – list (default: []); dictionaries containing the variables to be fixed in standard format

See also

set_fixed_variables()

EXAMPLES:

sage: from claasp.ciphers.block_ciphers.simon_block_cipher import SimonBlockCipher
sage: from claasp.cipher_modules.models.milp.milp_model import MilpModel
sage: simon = SimonBlockCipher(block_bit_size=32, key_bit_size=64, number_of_rounds=2)
sage: milp = MilpModel(simon)
sage: milp.init_model_in_sage_milp_class()
sage: fixed_variables = [{
....:    'component_id': 'plaintext',
....:    'constraint_type': 'equal',
....:    'bit_positions': [0, 1, 2, 3],
....:    'bit_values': [1, 0, 1, 1]
....: }, {
....:    'component_id': 'cipher_output_1_8',
....:    'constraint_type': 'not_equal',
....:    'bit_positions': [0, 1, 2, 3],
....:    'bit_values': [1, 1, 1, 0]
....: }]
sage: constraints = milp.fix_variables_value_constraints(fixed_variables)
sage: constraints
[x_0 == 1,
 x_1 == 0,
 x_2 == 1,
 x_3 == 1,
 x_4 == 1 - x_5,
 x_6 == 1 - x_7,
 x_8 == 1 - x_9,
 x_10 == x_11,
 1 <= x_4 + x_6 + x_8 + x_10]
init_model_in_sage_milp_class(solver_name='GLPK')

Initialize a MILP instance from the build-in sage class.

INPUT:

  • solver_name – string; the solver to call

EXAMPLES:

sage: from claasp.ciphers.block_ciphers.speck_block_cipher import SpeckBlockCipher
sage: from claasp.cipher_modules.models.milp.milp_model import MilpModel
sage: speck = SpeckBlockCipher(block_bit_size=32, key_bit_size=64, number_of_rounds=2)
sage: milp = MilpModel(speck)
sage: milp.init_model_in_sage_milp_class()
sage: milp._model
Mixed Integer Program (no objective, 0 variables, 0 constraints)
property integer_variable
property intermediate_output_names
property model
property model_constraints

Return the model specified by model_type.

INPUT:

  • model_type – string; the model to retrieve

EXAMPLES:

sage: from claasp.ciphers.block_ciphers.speck_block_cipher import SpeckBlockCipher
sage: from claasp.cipher_modules.models.milp.milp_model import MilpModel
sage: speck = SpeckBlockCipher(number_of_rounds=4)
sage: milp = MilpModel(speck)
sage: milp.model_constraints
Traceback (most recent call last):
...
ValueError: No model generated
property non_linear_component_id
solve(model_type, solver_name='GLPK', external_solver_name=None)

Return the solution of the model.

INPUT:

  • model_type – string; the model to solve

  • solver_name – string (default: GLPK); the solver to call when building the internal Sagemath MILP model. If no external solver is specified, solver_name will also be used to solve the model.

  • external_solver_name – string (default: None); if specified, the library will write the internal Sagemath MILP model as a .lp file and solve it outside of Sagemath, using the external solver.

EXAMPLES:

sage: from claasp.ciphers.block_ciphers.speck_block_cipher import SpeckBlockCipher
sage: from claasp.cipher_modules.models.milp.milp_models.milp_xor_differential_model import MilpXorDifferentialModel
sage: speck = SpeckBlockCipher(number_of_rounds=4)
sage: milp = MilpXorDifferentialModel(speck)
sage: milp.init_model_in_sage_milp_class()
sage: milp.add_constraints_to_build_in_sage_milp_class()
...
sage: solution = milp.solve("xor_differential") # random
solver_names(verbose=False)
weight_constraints(weight, weight_precision=2)

Return a list of variables and a list of constraints that fix the total weight to a specific value.

INPUT:

  • weight – integer; the total weight. If negative, no constraints on the weight is added

  • weight_precision – integer (default: 2); the number of decimals to use when rounding the weight of the trail.

EXAMPLES:

sage: from claasp.ciphers.block_ciphers.simon_block_cipher import SimonBlockCipher
sage: from claasp.cipher_modules.models.milp.milp_model import MilpModel
sage: simon = SimonBlockCipher(block_bit_size=32, key_bit_size=64, number_of_rounds=2)
sage: milp = MilpModel(simon)
sage: milp.init_model_in_sage_milp_class()
sage: variables, constraints = milp.weight_constraints(10)
sage: variables
[('p[probability]', x_0)]
sage: constraints
[x_0 == 1000]