def process_trace_set_paths(result,
trace_set_paths,
conf,
request_id=None,
keep_trace_sets=False):
num_todo = len(trace_set_paths)
num_done = 0
for trace_set_path in trace_set_paths:
# Get trace name from path
# trace_set_name = basename(trace_set_path)
logger.info("Processing '%s' (%d/%d)" %
(trace_set_path, num_done, num_todo))
# Load trace
trace_set = emio.get_trace_set(trace_set_path,
conf.format,
ignore_malformed=False,
remote=False)
if trace_set is None:
logger.warning(
"Failed to load trace set %s (got None). Skipping..." %
trace_set_path)
continue
# Process trace set
process_trace_set(result, trace_set, conf, request_id, keep_trace_sets)
num_done += 1
def compress_trace_set(trace_set_path):
if trace_set_path.endswith('.npy'):
parent_dataset_path = os.path.dirname(trace_set_path)
manifest_path = os.path.join(parent_dataset_path, 'manifest.emcap')
if os.path.exists(manifest_path):
# Open manifest
with open(manifest_path, 'rb') as manifest_file:
manifest = pickle.load(manifest_file)
conf = manifest['conf']
# Load trace set
trace_set = emio.get_trace_set(trace_set_path, 'cw', remote=False)
conf_delete_action(
conf, 'optimize_capture'
) # Make sure there is no optimize_capture action anymore
# Add appropriate actions
if 'pca' in manifest:
conf.actions.append(Action('pca[%s]' % manifest_path))
elif 'autoenc' in manifest:
conf.actions.append(Action('corrtest[autoenc]'))
# Perform compression
result = EMResult()
ops.process_trace_set(result,
trace_set,
conf,
keep_trace_sets=True)
processed_trace_set = result.trace_sets[0]
# Save compressed trace set
processed_trace_set.save(os.path.abspath(parent_dataset_path),
dry=False)
else:
raise EMMAException(
"No manifest.emcap in %s, so don't know how to compress." %
parent_dataset_path)
else:
raise EMMAException("Not a valid traceset_path in numpy format")
def remote_get_trace_set(trace_set_path, format, ignore_malformed):
return emio.get_trace_set(trace_set_path,
format,
ignore_malformed,
remote=False)
parser.add_argument("--limit",
type=int,
default=0,
help="Limit number of trace sets (0=infinite)")
args = parser.parse_args()
dataset_name = args.dataset_name
dataset_name_pca = dataset_name + "-pca"
# Gather signals
dataset = get_dataset(dataset_name, remote=False)
all_signals = []
for count, trace_set_path in enumerate(dataset.trace_set_paths):
print("\rGathering signal %d " % count)
trace_set_path = os.path.join(dataset.root, trace_set_path)
trace_set = get_trace_set(trace_set_path, "cw", remote=False)
for trace in trace_set.traces:
all_signals.append(trace.signal)
if count + 1 == args.limit:
break
all_signals = np.array(all_signals)
# Do PCA
print("Performing PCA")
pca = PCA()
pca.fit(all_signals)
# Save PCA model
with open("pca-components-%s.p" % dataset_name, 'wb') as f:
pickle.dump(pca, f)
print("Dumped PCA model to pca-components-%s.p" % dataset_name)
plt.plot(signal)
plt.show()
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Electromagnetic Mining Array (EMMA): Dataset visualization tool', formatter_class=argparse.RawDescriptionHelpFormatter)
parser.add_argument('dataset', type=str, help='Identifier of dataset to use', nargs='+')
parser.add_argument('--mean', default=False, action='store_true', help='Plot mean of signals')
args, unknown = parser.parse_known_args()
for dataset_name in args.dataset:
dataset = emio.get_dataset(dataset_name, remote=False)
print("Dataset: %s\nFormat: %s" % (dataset.id, dataset.format))
# Calculate mean
for trace_set_path in dataset.trace_set_paths:
trace_set = emio.get_trace_set(join(dataset.root, trace_set_path), dataset.format, ignore_malformed=False, remote=False)
if args.mean:
signals = []
for trace in trace_set.traces:
signals.append(trace.signal)
signals = np.array(signals)
plot_signal(np.mean(signals, axis=0))
else:
for trace in trace_set.traces:
print("Key: %s" % numpy_to_hex(trace.key))
print("Plaintext: %s" % numpy_to_hex(trace.plaintext))
print("---------------------------------------")
plot_signal(trace.signal)