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76552d6 033e4ff 76552d6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 | """
Shared utility functions for the ML-based cryptanalysis project.
"""
import numpy as np
import torch
import os
import json
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import seaborn as sns
# Reproducibility
SEED = 42
np.random.seed(SEED)
torch.manual_seed(SEED)
DEVICE = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
# Project paths
PROJECT_ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
def int_to_bits(val, nbits):
"""Convert integer to numpy bit array (MSB first)."""
return np.array([(val >> i) & 1 for i in range(nbits - 1, -1, -1)], dtype=np.float32)
def bits_to_int(bits):
"""Convert bit array back to integer."""
val = 0
for b in bits:
val = (val << 1) | int(b)
return val
def int_to_words(val, word_size, num_words):
"""Convert integer to word-level array."""
mask = (1 << word_size) - 1
words = []
for i in range(num_words - 1, -1, -1):
words.append((val >> (i * word_size)) & mask)
return np.array(words, dtype=np.float32)
def hamming_weight(val, nbits):
"""Compute Hamming weight of an integer."""
return bin(val & ((1 << nbits) - 1)).count('1')
def xor(a, b, nbits):
"""XOR two integers with bit masking."""
return (a ^ b) & ((1 << nbits) - 1)
def rotate_left(val, r, nbits):
"""Left rotation."""
return ((val << r) | (val >> (nbits - r))) & ((1 << nbits) - 1)
def rotate_right(val, r, nbits):
"""Right rotation."""
return ((val >> r) | (val << (nbits - r))) & ((1 << nbits) - 1)
def save_results(results, filepath):
"""Save results dictionary to JSON."""
os.makedirs(os.path.dirname(filepath), exist_ok=True)
# Convert numpy types
def convert(o):
if isinstance(o, (np.integer,)):
return int(o)
if isinstance(o, (np.floating,)):
return float(o)
if isinstance(o, np.ndarray):
return o.tolist()
return o
with open(filepath, 'w') as f:
json.dump(results, f, indent=2, default=convert)
#load results from JSON, converting lists back to numpy arrays where appropriate
def load_results(filepath):
"""Load results dictionary from JSON."""
with open(filepath, 'r') as f:
return json.load(f)
def setup_plot_style():
"""Set up consistent, publication-quality plot style."""
plt.style.use('seaborn-v0_8-whitegrid')
plt.rcParams.update({
'font.size': 12,
'axes.titlesize': 14,
'axes.labelsize': 12,
'xtick.labelsize': 10,
'ytick.labelsize': 10,
'legend.fontsize': 10,
'figure.figsize': (10, 6),
'figure.dpi': 150,
'savefig.dpi': 150,
'savefig.bbox': 'tight',
})
# Cipher registry
CIPHER_REGISTRY = {}
def register_cipher(name):
"""Decorator to register a cipher class."""
def decorator(cls):
CIPHER_REGISTRY[name] = cls
return cls
return decorator
def get_cipher(name):
"""Get a cipher class by name."""
if name not in CIPHER_REGISTRY:
raise ValueError(f"Unknown cipher: {name}. Available: {list(CIPHER_REGISTRY.keys())}")
return CIPHER_REGISTRY[name]
def list_ciphers():
"""List all registered ciphers."""
return list(CIPHER_REGISTRY.keys())
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