def show_nicv(values, traces, nr_digits=4):
""" Compute the Normalized Inter-Class Variance as in the article """
import numpy as np
values = np.array(values, dtype=np.uint8)
traces = np.array(traces)
from lascar import TraceBatchContainer, Session, NicvEngine, hamming
# Use the Hamming weight of leaked values and add some noise
# through the 'leakage_processing' parameter
t = TraceBatchContainer(
traces,
values,
leakage_processing=lambda x: np.array(
[hamming(i) for i in x], dtype=np.uint
)
+ np.random.normal(0, 0.5, len(x)),
)
s = Session(t)
## Input value leakage
# s.add_engines([NicvEngine('a'+str(i), lambda v,z=i:v[z], range(9)) for i in range(nr_digits)])
## Difference leakage
s.add_engines([NicvEngine('a'+str(i), lambda v,z=i:np.int8(v[z]) - np.int8(STORED_PIN[z]), range(-9,8)) for i in range(nr_digits)])
## below is a variant on the carry bit
# s.add_engines([NicvEngine('c'+str(i), lambda v,z=i:v[z]>int(STORED_PIN[z]), range(16)) for i in range(nr_digits)])
s.run()
return np.array([s[eng]._finalize() for eng in s.engines if eng not in ['mean', 'var']])
traces = tmp
## Phase 2 : attack with Lascar
## Launch 16 CPAs on the outputs of the sbox
from lascar.container import TraceBatchContainer
from lascar import Session, CpaEngine, ConsoleOutputMethod
from lascar.tools.aes import sbox
t = TraceBatchContainer(traces, values)
s = Session(t, output_method=ConsoleOutputMethod())
s.add_engines(
[
CpaEngine(f"cpa{i}", lambda v, k, z=i: sbox[v[z] ^ k], range(256))
for i in range(16)
]
)
s.run()
print(s.output_method.finalize())
# Check the results :
print("Key should be : f0 33 1c e0 26 6a da ce 86 a8 a1 3b fa 14 67 40")
K = list(
map(lambda x: int(x, 16), "f0 33 1c e0 26 6a da ce 86 a8 a1 3b fa 14 67 40".split())
)
for i, n in enumerate([f"cpa{i}" for i in range(16)]):
print(