json_data = open(args[0])
service_id = {'netflix':1,'gmail':1, 'background':1}
settings = json.load(json_data)
ts = time.time()
print 'start time :%f' % ts
max_levels = settings["max_levels"]
level_steps = settings["level_steps"]
obj_LogReg = [{} for x in range(0, max_levels)]
print "The maximum number of levels required by the filter %d" % (max_levels)
SUT = "netflix"
supervised_samples = {}
PCA = [None for x in range(0, max_levels)]
#session table, for known and unknown
known_flow_table = Flow_table(max_levels)
unknown_flow_table = Flow_table(max_levels)
rt = time.time()
pkt_filter = Pkt_len_filter()
bkgnd_sess = 0
#load the parameter file. the parameter file is expected to be a json file.
#exit if the parameter file doesn't contain
theta_params = {}
if ("parameters" in settings["files"] and options.learn == False):
for detail_coeff in level_steps:
try:
service_params_fd = open(settings["files"]["parameters"][detail_coeff], "r")
service_params = json.load(service_params_fd)
print "creating logistic regression object for level %d" % (detail_coeff)
for service_key in service_params:
parser.error("Incorrect number of arguments")
print "Opening JSON file %s" %(args[0])
json_data = open(args[0])
#Learn the applications from the input JSON file
service_id = {}#{'netflix':1,'gmail':1, 'background':1}
org_settings = json.load(json_data)
apps = org_settings["apps"];
max_levels = org_settings["max_levels"]
level_steps = org_settings["level_steps"]
SUT = None
print "Analysing the application found in %s" % (args[0])
for keys in apps:
service_id[keys] = 1
print "Found app:%s" % (keys)
#Initialize the flow table
pkt_flow_table = Flow_table(1)
#the packet filter, used for feature extraction on a packet.
pkt_filter = Pkt_len_filter()
#Parse the PCAP files and generate the statistics of the packets within a
#PCAP file.
for pcap_file_key in org_settings["apps"]:
for idx in range(0,len(org_settings["apps"][pcap_file_key])):
pcap_file = open(org_settings["apps"][pcap_file_key][idx], "r")
print "Processing PCAP file for service %s:%s" % (pcap_file_key, org_settings["apps"][pcap_file_key][idx])
for tx, pkt in dpkt.pcap.Reader(pcap_file):
#process the packet, generate coeffecients and update the flow
#table.
pkt_flow_table.process_pkt(pkt=pkt, \
pkt_filter=pkt_filter, service=pcap_file_key,\
sample_idx=idx, max_levels=max_levels)