import sys
import json
+import numpy as np
from collections import defaultdict
from dateutil import parser
JSON_KEY_FRAME_TIME = "frame.time"
TABLE_HEADER_X = "Timestamp (hh:mm:ss)"
TABLE_HEADER_Y = "Packet frequency (pps)"
+INCOMING_APPENDIX = "_incoming"
+OUTGOING_APPENDIX = "_outgoing"
+FILE_APPENDIX = ".dat"
+# Use this constant as a flag
+WINDOW_SIZE = 5
+USE_MOVING_AVERAGE = False
-def save_to_file(tbl_header, dictionary, filename_out):
+
+def moving_average(array, window=3):
+ """ Calculate moving average
+ Args:
+ array: array of numbers
+ window: window of moving average (default = 3)
+ Adapted from:
+ https://stackoverflow.com/questions/14313510/how-to-calculate-moving-average-using-numpy
+ """
+ # Check if window > len(array)
+ if window > len(array):
+ window = len(array)
+ # Calculate cumulative sum of each array element
+ retarr = np.cumsum(array, dtype=float)
+ # Adjust cumulative sum of each array element
+ # based on window size
+ retarr[window:] = retarr[window:] - retarr[:-window]
+ # Pad the first array elements with zeroes
+ retarr[:window - 1] = np.zeros(window - 1)
+ # Calculate moving average starting from the element
+ # at window size, e.g. element 4 for window=5
+ retarr[window - 1:] = retarr[window - 1:] / window
+ return retarr
+
+
+def save_to_file(tblheader, dictionary, filenameout):
""" Show summary of statistics of PCAP file
Args:
- tbl_header: header for the saved table
+ tblheader: header for the saved table
dictionary: dictionary to be saved
filename_out: file name to save
"""
# Appending, not overwriting!
- f = open(filename_out, 'a')
+ f = open(filenameout, 'a')
# Write the table header
- f.write("# " + TABLE_HEADER_X + " " + TABLE_HEADER_Y + "\n");
- # Iterate over dictionary and write (key, value) pairs
- for key in sorted(dictionary):
- # Comma separated
- #f.write(str(key) + ", " + str(dictionary[key]) + "\n")
- # Space separated
- f.write(str(key) + " " + str(dictionary[key]) + "\n")
+ f.write("# " + tblheader + "\n")
+ f.write("# " + TABLE_HEADER_X + " " + TABLE_HEADER_Y + "\n")
+ # Write "0 0" if dictionary is empty
+ if not dictionary:
+ f.write("0 0")
+ f.close()
+ print "Writing zeroes to file: ", filenameout
+ return
+ if USE_MOVING_AVERAGE:
+ # Use moving average if this flag is true
+ sortedarr = []
+ for key in sorted(dictionary):
+ sortedarr.append(dictionary[key])
+ valarr = moving_average(sortedarr, WINDOW_SIZE)
+ #print vallist
+ # Iterate over dictionary and write (key, value) pairs
+ ind = 0
+ for key in sorted(dictionary):
+ # Space separated
+ f.write(str(key) + " " + str(valarr[ind]) + "\n")
+ ind += 1
+ else:
+ # Iterate over dictionary and write (key, value) pairs
+ for key in sorted(dictionary):
+ # Space separated
+ f.write(str(key) + " " + str(dictionary[key]) + "\n")
f.close()
- print "Writing output to file: ", filename_out
+ print "Writing output to file: ", filenameout
def main():
print "Usage: python", sys.argv[0], "<input_file> <output_file> <device_name> <mac_address>"
return
# Parse the file for the specified MAC address
- time_freq = parse_json(sys.argv[1], sys.argv[4])
+ timefreq_incoming = parse_json(sys.argv[1], sys.argv[4], True)
+ timefreq_outgoing = parse_json(sys.argv[1], sys.argv[4], False)
# Write statistics into file
- save_to_file(sys.argv[3], time_freq, sys.argv[2])
print "====================================================================="
- #for time in time_freq.keys():
- for key in sorted(time_freq):
- print key, " => ", time_freq[key]
+ print "==> Analyzing incoming traffic ..."
+ save_to_file(sys.argv[3] + INCOMING_APPENDIX, timefreq_incoming, sys.argv[2] + INCOMING_APPENDIX + FILE_APPENDIX)
+ print "====================================================================="
+ print "==> Analyzing outgoing traffic ..."
+ save_to_file(sys.argv[3] + OUTGOING_APPENDIX, timefreq_outgoing, sys.argv[2] + OUTGOING_APPENDIX + FILE_APPENDIX)
print "====================================================================="
+ #for time in time_freq.keys():
+ #for key in sorted(time_freq):
+ # print key, " => ", time_freq[key]
+ #print "====================================================================="
# Convert JSON file containing DNS traffic to a map in which a hostname points to its set of associated IPs.
-def parse_json(file_path, mac_address):
+def parse_json(filepath, macaddress, incomingoutgoing):
""" Show summary of statistics of PCAP file
Args:
- file_path: path of the read file
- mac_address: MAC address of a device to analyze
+ filepath: path of the read file
+ macaddress: MAC address of a device to analyze
+ incomingoutgoing: boolean to define whether we collect incoming or outgoing traffic
+ True = incoming, False = outgoing
"""
# Maps timestamps to frequencies of packets
- time_freq = dict()
- with open(file_path) as jf:
+ timefreq = dict()
+ with open(filepath) as jf:
# Read JSON.
# data becomes reference to root JSON object (or in our case json array)
data = json.load(jf)
layers = p[JSON_KEY_SOURCE][JSON_KEY_LAYERS]
# Get timestamp
frame = layers.get(JSON_KEY_FRAME, None)
- date_time = frame.get(JSON_KEY_FRAME_TIME, None)
+ datetime = frame.get(JSON_KEY_FRAME_TIME, None)
# Get into the Ethernet address part
eth = layers.get(JSON_KEY_ETH, None)
# Skip any non DNS traffic
src = eth.get(JSON_KEY_ETH_SRC, None)
dst = eth.get(JSON_KEY_ETH_DST, None)
# Get just the time part
- date_time_obj = parser.parse(date_time)
+ datetimeobj = parser.parse(datetime)
# Remove the microsecond part
- time_str = str(date_time_obj.time())[:8]
- print str(time_str) + " - src:" + str(src) + " - dest:" + str(dst)
+ timestr = str(datetimeobj.time())[:8]
+ print str(timestr) + " - src:" + str(src) + " - dest:" + str(dst)
# Get and count the traffic for the specified MAC address
- if src == mac_address or dst == mac_address:
- # Check if timestamp already exists in the map
- # If yes, then just increment the frequency value...
- if time_str in time_freq:
- time_freq[time_str] = time_freq[time_str] + 1
- else: # If not, then put the value one there
- time_freq[time_str] = 1
- return time_freq
+ if incomingoutgoing:
+ if dst == macaddress:
+ # Check if timestamp already exists in the map
+ # If yes, then just increment the frequency value...
+ if timestr in timefreq:
+ timefreq[timestr] = timefreq[timestr] + 1
+ else: # If not, then put the value one there
+ timefreq[timestr] = 1
+ else:
+ if src == macaddress:
+ # Check if timestamp already exists in the map
+ # If yes, then just increment the frequency value...
+ if timestr in timefreq:
+ timefreq[timestr] = timefreq[timestr] + 1
+ else: # If not, then put the value one there
+ timefreq[timestr] = 1
+
+ return timefreq
+
if __name__ == '__main__':
main()
projects / pingpong.git / blobdiff