Run "python AI/genetic_algorithm.py" to see the results.

It uses genetic algorithms to find a good SBox.

Summary of files

AI/ classes.py - Has the functions for implementing the genetic algorithm
genetic_algorithm.py - Runs the genetic algorithm by taking the relative importance of the criteria as input.

DifferentialTables/
DDTs for all the SBoxes.

Implementation/ Implementation of the cipher and supporting scripts and functions.
A detailed readme for implementation can be found in thsi folder as "readme.txt".

LAT_DDT/ tables.py - Functions to generate LAT and DDT along with computing the scores.
DDT_generator.py - Generates DDT for all SBOXes present in "Sboxes" folder.
LAT_generator.py - Generates LAT for all SBOXes present in "Sboxes" folder.

Scores/ DDT_score.py - Computes the DDT score for an SBOX if the corresponding table is present in the "DifferentialTables" folder.
LAT_score.py - Computes the LAT score for an SBOX if the corresponding table is present in the "LinearTables" folder.
SBOX_score.py - Computes the scores for all criteria and outputs the average over all output bits of the SBOX.

LC_DC/ LC.py - Supporting functions for finding the deadliest linear and differential trail
main_LC.py - Code for computing the minimum number of rounds and the maximum bias for 20 rounds.
main_DC.py - Code for computing the minimum number of rounds(DC) and the maximum prop ratio for 20 rounds.

LinearTables/ LATs for all the SBoxes.

Sboxes/ Sboxes generated by the GA(8 of them).