def malware_train(line):
global malware_train_nb
if (mta.check_if_link_is_in_downloaded_file(line) is False):
pcap_file_name = mta.download_pcap([line])
for pcap in pcap_file_name:
if (pcap is not None):
if (check_if_already_trained(pcap) is False):
attacker = AttackerCalc(pcap=mta.get_folder_name() + "/" +
pcap)
ip_to_consider = attacker.compute_attacker()
flow_type = "malware"
filter_1.set_ip_whitelist_filter(ip_to_consider)
filter_2.set_ip_whitelist_filter(ip_to_consider)
filter_3.set_ip_whitelist_filter(ip_to_consider)
featuresCalc = FeaturesCalc(flow_type=flow_type,
min_window_size=5)
csv = CSV(file_name="features_" + flow_type,
folder_name="Features")
csv.create_empty_csv()
csv.add_row(featuresCalc.get_features_name())
argument = {
"features_calc": featuresCalc,
"packets": [],
'filter': [filter_1, filter_2, filter_3],
'csv_obj': csv
}
sniffer = Sniffer(iface_sniffer,
callback_prn=callback_sniffer,
callback_prn_kwargs=argument)
sniffer.start()
while (sniffer.get_started_flag() is False):
pass
try:
sender = Sender(iface_sender,
fast=False,
verbose=False,
time_to_wait=10)
sender.send(mta.get_folder_name() + "/" + pcap)
sniffer.stop()
except Exception as e:
print(e)
csv.close_csv()
env.set_csv(csv.get_folder_name() + "/" +
csv.get_current_file_name())
agent.train_agent(
steps=csv.get_number_of_rows() - 1,
log_interval=csv.get_number_of_rows() - 1,
verbose=2,
nb_max_episode_steps=csv.get_number_of_rows() - 1)
malware_train_nb -= 1
trained_file.write(pcap + "\n")
else:
print("\nPcap gia' utilizzato in passato. Saltato.\n")
else:
pass
else:
pass
def legitimate_train(line):
global legitimate_train_nb
if (check_if_already_trained(line) is False):
flow_type = "legitimate"
filter_1.set_ip_whitelist_filter([])
filter_2.set_ip_whitelist_filter([])
filter_3.set_ip_whitelist_filter([])
featuresCalc = FeaturesCalc(flow_type=flow_type, min_window_size=5)
csv = CSV(file_name="features_" + flow_type, folder_name="Features")
csv.create_empty_csv()
csv.add_row(featuresCalc.get_features_name())
argument = {
"features_calc": featuresCalc,
"packets": [],
'filter': [filter_1, filter_2, filter_3],
'csv_obj': csv
}
sniffer = Sniffer(iface_sniffer,
callback_prn=callback_sniffer,
callback_prn_kwargs=argument)
sniffer.start()
while (sniffer.get_started_flag() is False):
pass
try:
sender = Sender(iface_sender,
fast=False,
verbose=False,
time_to_wait=10)
sender.send(lg.get_folder_name() + "/" + line)
sniffer.stop()
except Exception as e:
print(e)
csv.close_csv()
env.set_csv(csv.get_folder_name() + "/" + csv.get_current_file_name())
agent.train_agent(steps=csv.get_number_of_rows() - 1,
log_interval=csv.get_number_of_rows() - 1,
verbose=2,
nb_max_episode_steps=csv.get_number_of_rows() - 1)
legitimate_train_nb -= 1
trained_file.write(line + "\n")
else:
print("\nPcap gia' utilizzato in passato. Saltato.\n")
