Added fix for trail search and vectorized evaluation

claasp/cipher_modules/generic_functions_vectorized_bit.py

@@ -80,7 +80,7 @@ def bit_vector_select_word(input, bits, verbosity=False):
     return output
 
 
-def bit_vector_SBOX(input, sbox, verbosity=False):
+def bit_vector_SBOX(input, sbox, verbosity=False, output_bit_size = None):
     """
     Computes the SBox operation on binary values.
 
@@ -95,6 +95,10 @@ def bit_vector_SBOX(input, sbox, verbosity=False):
     int_val = np.packbits(tmp, axis=0)
     int_output = sbox[int_val]
     output = np.unpackbits(int_output, axis=0)
+    if output_bit_size is None:
+        output = output[-input.shape[0]:]
+    else:
+        output = output[-output_bit_size:]
     if verbosity:
         print("SBox")
         print("Input : ", input.transpose())
@@ -103,7 +107,7 @@ def bit_vector_SBOX(input, sbox, verbosity=False):
         print("Output : ", output.transpose())
         print("---")
 
-    return output[-input.shape[0]:]
+    return output
 
 
 def bit_vector_XOR(input, number_of_inputs, output_bit_size, verbosity=False):

claasp/cipher_modules/models/cp/cp_models/cp_xor_linear_model.py

@@ -613,8 +613,9 @@ def update_sbox_lat_valid_probabilities(self, component, valid_probabilities):
             for i in range(sbox_lat.nrows()):
                 set_of_occurrences = set(sbox_lat.rows()[i])
                 set_of_occurrences -= {0}
-                valid_probabilities.update({round(100 * math.log2(2 ** input_size / abs(occurrence)))
-                                            for occurrence in set_of_occurrences})
+                valid_probabilities.update(
+                    {round(100 * math.log2(abs(pow(2, input_size - 1) / occurence))) for occurence in
+                     set_of_occurrences})
             self.sbox_mant.append((description, output_id_link))
 
     def weight_xor_linear_constraints(self, weight):

claasp/components/sbox_component.py

@@ -100,8 +100,7 @@ def cp_update_lat_valid_probabilities(component, valid_probabilities, sbox_mant)
         for i in range(sbox_lat.nrows()):
             set_of_occurrences = set(sbox_lat.rows()[i])
             set_of_occurrences -= {0}
-            valid_probabilities.update({round(100 * math.log2(2 ** input_size / abs(occurrence)))
-                                        for occurrence in set_of_occurrences})
+            valid_probabilities.update({round(100 * math.log2(abs(pow(2, input_size - 1) / occurence))) for occurence in set_of_occurrences})
         sbox_mant.append((description, output_id_link))
 
 
@@ -698,7 +697,7 @@ def get_bit_based_vectorized_python_code(self, params, convert_output_to_bytes):
         sbox_params = [f'bit_vector_select_word({self.input_id_links[i]},  {self.input_bit_positions[i]})'
                        for i in range(len(self.input_id_links))]
         return [f'  {self.id} = bit_vector_SBOX(bit_vector_CONCAT([{",".join(sbox_params)} ]), '
-                f'np.array({self.description}, dtype=np.uint8))']
+                f'np.array({self.description}, dtype=np.uint8), output_bit_size = {self.output_bit_size})']
 
     def get_byte_based_vectorized_python_code(self, params):
         return [f'  {self.id} = byte_vector_SBOX({params}, np.array({self.description}, dtype=np.uint8))']