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SimpleMeanDiff.py
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from TunnelMiner import TunnelMiner
import logging
import math
import numpy as np
import random
from collections import Counter
from collections import OrderedDict
class SimpleMeanDiff(object):
def __init__(self, test_data_lbl):
# Configure Logging
logging.basicConfig(level=logging.INFO)
# logging.basicConfig(level=logging.WARNING)
self.logger = logging.getLogger(__name__)
# self.logger.setLevel(logging.INFO)
self.logger.setLevel(logging.DEBUG)
# self.logger.setLevel(logging.WARNING)
# Load the test data sets ----------------------------------
self.test_dataset_label = test_data_lbl
self.test_dataset = TunnelMiner()
if self.test_dataset_label == "HTTPovDNS-Static":
self.test_dataset.load_sub_dataset("HTTPovDNS-Static", "All")
# self.http_data.load_sub_dataset("http-ovDNS-test2", "All")
if self.test_dataset_label == "FTPovDNS-DL":
self.test_dataset.load_sub_dataset("FTPovDNS-DL", "All")
# self.ftp_data.load_sub_dataset("ftp-ovDNS-test-old", "All")
if self.test_dataset_label == "HTTP-S-ovDNS-Static":
self.test_dataset.load_sub_dataset("HTTP-S-ovDNS-Static", "All")
if self.test_dataset_label == "POP3ovDNS-DL-5txt-ATT":
#self.test_dataset.load_sub_dataset("POP3ovDNS-DL", "All")
self.test_dataset.load_sub_dataset("POP3ovDNS-DL-5txt-ATT", "All")
# Load the ground truth values -----------------------------
self.http_ground = TunnelMiner()
self.http_ground.load_sub_dataset("HTTP-ground","HTTP-Req-Bytes-Hex")
self.ftp_ground = TunnelMiner()
self.ftp_ground.load_sub_dataset("FTP-ground", "FTP-Req-Bytes-Hex")
self.http_s_ground = TunnelMiner()
self.http_s_ground.load_sub_dataset("HTTP-S-ground", "HTTP-S-Req-Bytes-Hex")
self.pop3_ground = TunnelMiner()
self.pop3_ground.load_sub_dataset("POP3-ground", "POP3-Req-Bytes-Hex")
def do_mean_diff(self, testCapList, grndTruthList, sampleRounds):
runningSum = []
if sampleRounds > 0:
for i in range(sampleRounds):
twoSampleSet = self.getTwoEquiLenSamples(testCapList, grndTruthList)
runningSum.append(self.calcMeanDiff(twoSampleSet))
self.logger.debug("Running Sum Len: %i" % len(runningSum))
avg = np.average(runningSum)
return avg
def calcMeanDiff(self, twoSampleDict):
meanTestSeq = np.average(twoSampleDict['testSeq'])
meanGrndTruthSeq = np.average(twoSampleDict['grndTruthSeq'])
meanDiff = abs(meanTestSeq - meanGrndTruthSeq)
return meanDiff
def get_Mean_Diff_Avg_Score_n_predict(self):
predictions = []
# Compare AGAINST http
against_http_score = []
# # Change the variable here depending on whether it is the HTTP dataset being tested or the FTP dataset
for single_pcap_entropy_list in self.test_dataset.get_list_of_Entropy_lists():
self.logger.debug("In 'get_Mean_Diff_Avg_Score_n_predict' ...")
self.logger.debug("Length of Single PCAP list of entropies: %i" % len(single_pcap_entropy_list))
ground_truth_list_of_lists_http = self.http_ground.get_list_of_Entropy_lists()
self.logger.debug("Length of HTTP Ground-Truth List of lists: --> %i" % len(ground_truth_list_of_lists_http))
self.logger.debug("Length of HTTP Ground-Truth List within List: --> %i" % len(ground_truth_list_of_lists_http[0]))
against_http_score.append(self.do_mean_diff(single_pcap_entropy_list, ground_truth_list_of_lists_http[0], 100))
# Compare AGAINST ftp
against_ftp_score = []
# # Change also HERE
for single_pcap_entropy_list in self.test_dataset.get_list_of_Entropy_lists():
grndTruth_list_of_lists_ftp = self.ftp_ground.get_list_of_Entropy_lists()
self.logger.debug("Length of FTP Ground-Truth List of lists: --> %i" % len(grndTruth_list_of_lists_ftp))
self.logger.debug("Length of FTP Ground-Truth List within List: --> %i" % len(grndTruth_list_of_lists_ftp[0]))
against_ftp_score.append(self.do_mean_diff(single_pcap_entropy_list, grndTruth_list_of_lists_ftp[0], 100))
# Compare AGAINST http-s
against_http_s_score = []
# # Change also HERE
for single_pcap_entropy_list in self.test_dataset.get_list_of_Entropy_lists():
grndTruth_list_of_lists_http_s = self.http_s_ground.get_list_of_Entropy_lists()
self.logger.debug("Length of HTTP-S Ground-Truth List of lists: --> %i" % len(grndTruth_list_of_lists_http_s))
self.logger.debug(
"Length of HTTP-S Ground-Truth List within List: --> %i" % len(grndTruth_list_of_lists_http_s[0]))
against_http_s_score.append(self.do_mean_diff(single_pcap_entropy_list, grndTruth_list_of_lists_http_s[0], 100))
# Compare AGAINST pop3
against_pop3_score = []
# # Change also HERE
for single_pcap_entropy_list in self.test_dataset.get_list_of_Entropy_lists():
grndTruth_list_of_lists_pop3 = self.pop3_ground.get_list_of_Entropy_lists()
self.logger.debug("Length of POP3 Ground-Truth List of lists: --> %i" %
len(grndTruth_list_of_lists_pop3))
self.logger.debug("Length of POP3 Ground-Truth List within List: --> %i" %
len(grndTruth_list_of_lists_pop3[0]))
against_pop3_score.append(self.do_mean_diff(single_pcap_entropy_list, grndTruth_list_of_lists_pop3[0], 100))
self.logger.debug("HTTP Mean Diff scores len: %i" % len(against_http_score))
self.logger.debug("FTP Mean Diff scores len: %i" % len(against_ftp_score))
self.logger.debug("HTTP-S Mean Diff scores len: %i" % len(against_http_s_score))
self.logger.debug("POP3 Mean Diff scores len: %i" % len(against_pop3_score))
all_4_scores = {"vs_http": against_http_score, "vs_ftp": against_ftp_score,
"vs_http_s": against_http_s_score, "vs_pop3": against_pop3_score}
predictions = self.do_Score_Comparison(all_4_scores)
return predictions
def do_Score_Comparison(self, all_scores):
http_score_list = all_scores['vs_http']
ftp_score_list = all_scores['vs_ftp']
http_s_score_list = all_scores['vs_http_s']
pop3_score_list = all_scores['vs_pop3']
self.logger.debug("HTTP score List Len: %i" % len(http_score_list))
self.logger.debug("FTP score List Len: %i" % len(ftp_score_list))
self.logger.debug("HTTP_S score List Len: %i" % len(http_s_score_list))
self.logger.debug("POP3 score List Len: %i" % len(pop3_score_list))
prediction_list = []
if len(http_score_list) == len(ftp_score_list) and len(http_s_score_list) == len(pop3_score_list):
for count, http_sc_val in enumerate(http_score_list):
# print("UNRANKED:")
# print("----------------------------")
# print("UNRANKED: HTTP: %.3f | FTP: %.3f | HTTP_S: %.3f | POP3: %.3f" %
# (float(http_sc_val), float(ftp_score_list[count]),
# float(http_s_score_list[count]), float(pop3_score_list[count])))
# # METHOD 1 : Choosing which is the smallest value
# # -----------------------------------------------
# if float(http_sc_val) < float(ftp_score_list[count] and
# float(http_sc_val) < float(http_s_score_list[count]) and
# float(http_sc_val) < float(pop3_score_list[count])):
# prediction_list.append("HTTP")
# elif float(ftp_score_list[count]) < float(http_s_score_list[count]) and float(pop3_score_list[count]):
# prediction_list.append("FTP")
# elif float(http_s_score_list[count]) < float(pop3_score_list[count]):
# prediction_list.append("HTTPS")
# else:
# prediction_list.append("POP3")
# # METHOD 2 : Choosing the smallest value
# # ------------------------------------------------
# indexed_score_list = [http_sc_val, ftp_score_list[count], http_s_score_list[count], pop3_score_list[count]]
# lowest_index = indexed_score_list.index(min(indexed_score_list))
# if lowest_index == 0: # HTTP
# prediction_list.append("HTTP")
# elif lowest_index == 1: # FTP
# prediction_list.append("FTP")
# elif lowest_index == 2: # HTTP_S
# prediction_list.append("HTTPS")
# elif lowest_index == 3: # POP3
# prediction_list.append("POP3")
# # "METHOD 3" : Ranking all values and choosing the smallest value through the min function
# # ----------------------------------------------------
# ordered_score_dict = OrderedDict([('http', http_sc_val),
# ('ftp',ftp_score_list[count]),
# ('https', http_s_score_list[count]),
# ('pop3', pop3_score_list[count])])
score_dict = {'HTTP': float('%.3f'%(http_sc_val)), 'FTP': float('%.3f'%(ftp_score_list[count])),
'HTTPS': float('%.3f'%(http_s_score_list[count])), 'POP3': float('%.3f'%(pop3_score_list[count]))}
prediction_list.append(min(score_dict, key=score_dict.get))
ranked_score_dict = OrderedDict(sorted(score_dict.items(), key=lambda t: t[1]))
print("RANKED: %s" % ranked_score_dict)
else:
self.logger.debug("Something wrong with length of score lists")
self.logger.debug("HTTP Score list len: %i" % len(http_score_list))
self.logger.debug("FTP Score list len: %i" % len(ftp_score_list))
self.logger.debug("HTTP-S Score list len: %i" % len(http_s_score_list))
self.logger.debug("POP3 Score list len: %i" % len(pop3_score_list))
return prediction_list
def getEquiSampleLen(self, fullTestSeq, fullGrndTruthSeq):
'''
- Determines the lengths of the two sequences
- Selects 90% of the packets of the shorter sample (used 95% at some point)
:return:
'''
newSeqLen = (int(math.ceil(0.90 * len(fullTestSeq))) #originally this value was 0.95 ... then changed to 0.90, 0.80, 0.70
if len(fullTestSeq) < len(fullGrndTruthSeq)
else int(math.ceil(0.90 * len(fullGrndTruthSeq))))
# print("New Equalized Sequence Length: ", newSeqLen)
return newSeqLen
def getTwoEquiLenSamples(self, fullTestSeq, fullGrndTruthSeq):
'''
Given the new equivalent sample length from getEquiSampleLen():
- Randomly select a continuous sequence of values of the given length between Packet 1 and the length of the Packet
- Returns 2 samples of the same length; one from the test sample and one from the "ground truth"
:return: A Dictionary containing the 2 list/seq samples (testSeq,grndTruthSeq)
'''
self.logger.debug("Full-Test-Seq Len: %i" % len(fullTestSeq))
self.logger.debug("Full-Grnd-Truth-Seq Len: %i" % len(fullGrndTruthSeq))
if len(fullTestSeq) <= 1:
self.logger.warning('Test Seqence length is Zero')
exit()
elif len(fullGrndTruthSeq) <= 1:
self.logger.warning('Grnd Truth Seqence length is Zero')
exit()
newSeqLen = self.getEquiSampleLen(fullTestSeq, fullGrndTruthSeq)
self.logger.debug('New Equalized Sequence Length: %i' % newSeqLen)
testSeqStart = random.randint(1, len(fullTestSeq) - newSeqLen)
self.logger.debug('Sample Test Seq Starting Point: %i' % testSeqStart)
maxEnd_Grnd_Seq = len(fullGrndTruthSeq) - newSeqLen
self.logger.debug('Grnd Truth Seq Max End Point: %i' % maxEnd_Grnd_Seq)
if maxEnd_Grnd_Seq < 1:
grndTruthSeqStart = 1
newTestSeqList = fullTestSeq[testSeqStart:testSeqStart + (newSeqLen - 1)]
newgrndTruthSeqList = fullGrndTruthSeq[grndTruthSeqStart:grndTruthSeqStart + (newSeqLen - 1)]
else:
grndTruthSeqStart = random.randint(1, len(fullGrndTruthSeq) - newSeqLen)
newTestSeqList = fullTestSeq[testSeqStart:testSeqStart + newSeqLen]
newgrndTruthSeqList = fullGrndTruthSeq[grndTruthSeqStart:grndTruthSeqStart + newSeqLen]
self.logger.debug('Ground Truth Seq Starting Point: %i' % grndTruthSeqStart)
multiSampleSeq = dict(testSeq=[], grndTruthSeq=[])
multiSampleSeq["testSeq"] = newTestSeqList
multiSampleSeq["grndTruthSeq"] = newgrndTruthSeqList
# print("Test X: ", self.twoTestSamples["testSeq"])
# print("Test Y: ", self.twoTestSamples["grndTruthSeq"])
return multiSampleSeq
#mean_diff_tester = SimpleMeanDiff("FTPovDNS-DL")
#mean_diff_tester = SimpleMeanDiff("HTTPovDNS-Static")
#mean_diff_tester = SimpleMeanDiff("HTTP-S-ovDNS-Static")
mean_diff_tester = SimpleMeanDiff("POP3ovDNS-DL-5txt-ATT")
the_predictions = mean_diff_tester.get_Mean_Diff_Avg_Score_n_predict()
# the_predictions = mean_diff_tester.get_Mean_Diff_Avg_Score_n_predict('ftp')
# the_predictions = mean_diff_tester.get_Mean_Diff_Avg_Score_n_predict('http')
# the_predictions = mean_diff_tester.get_Mean_Diff_Avg_Score_n_predict('http_s')
# the_predictions = mean_diff_tester.get_Mean_Diff_Avg_Score_n_predict('pop3')
print(the_predictions)
print(Counter(the_predictions))