Brice Colombier / Side-channel traces preprocessing

Commit 1929d313581c4ff09b23cdfd22803992378478fd

Authored by Brice COLOMBIER almost 2 years ago

Exists in master

Add memory info to pairwise_operation

Showing 6 changed files with 62 additions and 46 deletions

average.py
check_ram.py
npy_to_raw.py
pairwise_operation.py
plot.py
realign.py

	1	+import numpy as np
	2	+import argparse
	3	+import os
	4	+
	5	+import matplotlib.pyplot as plt
	6	+
	7	+def realign(traces_file):
	8	+ traces = np.load(traces_file)
	9	+ averaged_traces = np.mean(traces, axis=0)
	10	+ print np.shape(averaged_traces)
	11	+ dirname, filename = os.path.split(args.traces_file)
	12	+ np.save(os.path.join(dirname, "averaged_"+filename), averaged_traces[None,:])
	13	+
	14	+if __name__ == "__main__":
	15	+
	16	+ # Parsing arguments
	17	+ parser = argparse.ArgumentParser(description='Preprocess traces')
	18	+ parser.add_argument("traces_file", type=str)
	19	+ args = parser.parse_args()
	20	+ realign(args.traces_file)

1		-import psutil
2		-
3		-import logging as log
4		-import argparse
5		-
6		-def check_ram(nb_samples, sample_size, verbose=False):
7		-
8		- if verbose:
9		- log.basicConfig(format="%(levelname)s: %(message)s", level=log.DEBUG)
10		- log.info("Verbose output enabled")
11		- else:
12		- log.basicConfig(format="%(levelname)s: %(message)s")
13		- available = psutil.virtual_memory().available
14		- log.info("{0} bits available".format(available))
15		- to_store = nb_samples*sample_size
16		- log.info("{0} bits to store".format(to_store))
17		- if to_store < available:
18		- return True
19		- else:
20		- log.warning("Not enough RAM available to store all the samples")
21		- return False
22		-
23		-if __name__ == "__main__":
24		-
25		- parser = argparse.ArgumentParser(description='Check RAM availability')
26		- parser.add_argument("--nb_samples", type=int)
27		- parser.add_argument("--sample_size", type=int)
28		- parser.add_argument('-v', '--verbose', action='store_true')
29		- args = parser.parse_args()
30		- print check_ram(args.nb_samples, args.sample_size, args.verbose)

	1	+import numpy as np
	2	+
	3	+import argparse
	4	+import os
	5	+
	6	+def npy_to_raw(traces_name):
	7	+ traces = np.load(traces_name)
	8	+
	9	+ print traces
	10	+
	11	+ dirname, filename = os.path.split(traces_name)
	12	+ filename, extension = os.path.splitext(filename)
	13	+
	14	+ traces.tofile(os.path.join(dirname, filename)+'.raw',
	15	+ sep = "",
	16	+ format = "%s")
	17	+
	18	+if __name__ == "__main__":
	19	+
	20	+ # Parsing arguments
	21	+ parser = argparse.ArgumentParser(description='Preprocess traces')
	22	+ parser.add_argument("traces_name", type=str)
	23	+ args = parser.parse_args()
	24	+
	25	+ npy_to_raw(args.traces_name)

1	1	# Imports for processing
2	2	import numpy as np
3	3	from skimage.util.shape import view_as_windows
4		-import check_ram
5	4
6	5	# Imports for parallel processing
7	6	from multiprocessing import Pool, current_process
8	7
9	8
...	...	@@ -63,16 +62,18 @@
63	62	for current_start_index in xrange(nb_samples - current_distance):
64	63	if first_chunk or (not first_chunk and current_start_index+current_distance>=window_size-1):
65	64	preprocessed_trace_length+=1
	65	+ log.info("Original traces occupying {0} Mbytes".format(traces.nbytes/1000000))
	66	+ increase = preprocessed_trace_length/np.shape(traces)[1]
	67	+ log.info("Preprocessed traces will occupy {0}x more memory".format(increase))
	68	+ log.info("Preprocessed traces will occupy {0} Mbytes".format(increase*traces.nbytes/1000000))
	69	+ bla
66	70	# Allocate memory for the preprocessed trace
67		- if not check_ram.check_ram(preprocessed_trace_length, 64):
68		- raise MemoryError("The preprocessed trace, consisting in {0} samples of {1} bits, cannot be stored in RAM".format(preprocessed_trace_length, 64))
69		- else:
70		- log.info('This will occupy {0} Mo in RAM'.format(round(preprocessed_trace_length/(1024*1024))))
71	71	preprocessed_trace = np.zeros((preprocessed_trace_length, nb_traces), dtype=dtype)
72	72	current_index = 0
73	73	indexes = np.zeros((preprocessed_trace_length),dtype='i,i')
74	74	# For all possible start indices in the window
75	75	for current_distance in xrange(minimum_distance, window_size):
	76	+ print current_distance
76	77	for current_start_index in xrange(nb_samples - current_distance):
77	78	if first_chunk or (not first_chunk and current_start_index+current_distance>=window_size-1):
78	79	value = np.array(operation(traces[:,current_start_index], traces[:,current_start_index+current_distance]), ndmin=2)
...	...	@@ -80,7 +81,7 @@
80	81	preprocessed_trace[current_index,:] = np.transpose(value)[:,0]
81	82	indexes[current_index] = (start_index+current_start_index, start_index+current_start_index+current_distance)
82	83	# Increase the running index
83		- if current_index in [16290, 17685, 16304, 16436, 16318, 16450, 16332, 16464]:
	84	+ if current_index in []:
84	85	print current_index
85	86	print current_start_index
86	87	print current_distance

...	...	@@ -5,14 +5,15 @@
5	5
6	6	def plot(traces_file, nb_subplots=1):
7	7	traces = np.load(traces_file)
8		- points_of_interest = [(21, 66),
9		- (35, 66),
10		- (49, 66),
11		- (63, 66),
12		- (167, 66),
13		- (181, 66),
14		- (195, 66),
15		- (153, 72)]
	8	+ # points_of_interest = [(21, 66),
	9	+ # (35, 66),
	10	+ # (49, 66),
	11	+ # (63, 66),
	12	+ # (167, 66),
	13	+ # (181, 66),
	14	+ # (195, 66),
	15	+ # (153, 72)]
	16	+ points_of_interest = []
16	17	colors = {66:'#1250D2',
17	18	72:'#C21637'}
18	19	if nb_subplots>1:

...	...	@@ -24,7 +24,7 @@
24	24	# Parsing arguments
25	25	parser = argparse.ArgumentParser(description='Preprocess traces')
26	26	parser.add_argument("traces_file", type=str)
27		- parser.add_argument("-r", "--ref_trace_index", type=int)
	27	+ parser.add_argument("-r", "--ref_trace_index", type=int, default=0)
28	28	args = parser.parse_args()
29	29	realign(args.traces_file, args.ref_trace_index)