import pandas as pd  # Pandas dataframe
from scapy.layers.dot11 import Dot11ProbeReq, Dot11Beacon
from scapy.utils import rdpcap
import seaborn as sns
import numpy as np
import os
from datetime import datetime
import matplotlib.pyplot as plt

MAX_SN = 4096  # Max value for the 802.11 sequence number

def extractSN(sc):
    hexSC = '0' * (4 - len(hex(sc)[2:])) + hex(sc)[2:]  # "normalize" to four digit hexadecimal number
    sn = int(hexSC[:-1], 16)
    return sn

'''
addr1   Destination MAC address
addr2   Source MAC address of sender
addr3   MAC address of Access Point
'''

filename = "raw_data/anecoica_20_01/01_prova.pcapng"

pcap = rdpcap(filename)

def derandomization_with_seq(pcap):
    packet = []
    ap = []
    mac_in_chiaro = []
    access_point = []
    time_list = [p.time for p in pcap]
    time_list = np.array(time_list)
    time_threshold = time_list.min() + (15 * 60)
    for pkt in pcap:
        ##### rimozione primi 5 minuti di scansione ############
        if pkt.time > time_threshold:
            # if pkt.haslayer(Dot11Beacon or Dot11ProbeResp or Dot11AssoResp):
            if pkt.haslayer(Dot11Beacon):
                if hasattr(pkt, 'addr2'):
                    ap.append(pkt.addr2)
                    # print("source address :", pkt.addr2)
                if hasattr(pkt, 'addr1') and pkt.addr1 != 'ff:ff:ff:ff:ff:ff':
                    mac_in_chiaro.append(pkt.addr1)
                    # print("mac in chiaro: ", pkt.addr1)
                if hasattr(pkt, 'addr3'):
                    access_point.append(pkt.addr3)
                    # print("Access Point address :", pkt.addr3)

            if pkt.haslayer(Dot11ProbeReq):

                mac = pkt.addr2
                seq = extractSN(pkt.SC)
                power = pkt.dBm_AntSignal
                # print("pkt", mac)
                while pkt:
                    if ('ID' and 'len' and 'info') in pkt.fields.keys():
                        packet.append([mac, seq, pkt.fields['ID'], pkt.fields['len'], power, pkt.time])
                    pkt = pkt.payload

    pkts_df = pd.DataFrame(packet)
    pkts_df = pkts_df.drop_duplicates()
    pkts_df.sort_values(by=[0, 1])
    pkts_df.columns = ['mac', 'seq', 'id', 'len', 'power', 'time']

    ap = set(ap)

    # print(len(pkts_df.mac.unique()))

    pkts_df = pkts_df[~pkts_df.mac.isin(ap)]

    # print(len(pkts_df.mac.unique()))

    # pkts_df = pkts_df[pkts_df.id != 221] # Wi-Fi Protected Access
    # pkts_df = pkts_df[pkts_df.id != 0]
    # pkts_df = pkts_df[pkts_df.id != 238]
    # prova = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 42, 48, 50]
    # pkts_df = pkts_df[pkts_df.id.isin(prova)]

    return ap, mac_in_chiaro, pkts_df

ap, mac_in_chiaro, df = derandomization_with_seq(pcap)

print("Number of packets : ", len(df))
print("Number of AP mac : ", len(ap))
print("Number of mac_in_chiaro : ", len(mac_in_chiaro))
print("Number of mac : ", len(df.mac.unique()))

## Randomico o no
df['random'] = df['mac'].apply(lambda x: (bin(int(x[:2], 16))[2:].zfill(8)[6:] in ['10', '11']))

print("MAC non randomici: ", len(df[df.random == False].mac.unique()))
print("MAC randomici: ", len(df[df.random == True].mac.unique()))


df_rand = df[df.random == True]

df_mac_list = df_rand.iloc[:1000]

#
start_df = 0

df_testing = df_mac_list.iloc[800:870]

ax = sns.catplot(x='time', y='seq', hue='mac', data=df_testing)
ax.fig.suptitle('Title')

plt.show()


df_testing = df_mac_list.iloc[800:900]

ax = sns.catplot(x='time', y='seq', hue='mac', data=df_testing)
ax.fig.suptitle('Title')

plt.show()

print(df_testing.head())

# for period in range(100, 1000, 100):
#
#     df_testing = df_mac_list.iloc[start_df:period]
#
#     ax = sns.catplot(x='time', y='seq', hue='mac', data=df_testing)
#     ax.fig.suptitle('{:d}{:d}'.format(start_df,period))
#
#     plt.show()
#
#     start_df = period



#df_mac_list = df_rand.loc[(df_rand['id'] == 50) & (df_rand['len'] == 4)].iloc[:50]

#sns.catplot(x='time', y='seq', hue='mac', data=df_mac_list)