import os
import time
import pandas as pd
import numpy as np
import joblib
import threading
import re
from scapy.all import *

features=['Bwd PSH Flags','Bwd IAT Mean','PSH Flag Cnt','Bwd IAT Max','Flow IAT Min','Bwd Pkt Len Max',
'Fwd IAT Mean','Bwd IAT Tot','Bwd IAT Std','Bwd Header Len','Subflow Bwd Byts','TotLen Bwd Pkts',
'Pkt Len Var','Flow IAT Std','Pkt Len Std','Pkt Len Min','Pkt Len Mean','Fwd IAT Max','Pkt Size Avg',
'Active Min','Bwd IAT Min','Init Bwd Win Byts','Active Std','Fwd Act Data Pkts','Idle Mean','Idle Max']

match_str='\"method\" ?: ?\"(mining\.authorize|mining\.get_transactions' \
          '|mining\.subscribe|mining\.submit|getblocktemplate|submitblock' \
          '|authorize|get_transactions|subscribe|submit|mining\.notify|mining\.set_difficulty' \
          '|notify|set_difficulty)\"'

model_cart = joblib.load('cart.dat')
model_id3 = joblib.load('id3.dat')

def os_cmd(i):
    cmd_tshark='sudo tshark -i eno2np1 -a duration:600 -f "net 10.201.0.0/16" -F pcap -w number'+str(i)+'.pcap'
    print(cmd_tshark)
    os.system(cmd_tshark)
    cmd_cic='cd /home/test1/CICFlowMeter-4.0/bin && ./cfm '+'data/number'+str(i)+'.pcap'+' data/csv/'
    print(cmd_cic)
    os.system(cmd_cic)
    testdf='/home/test1/CICFlowMeter-4.0/bin/data/csv/number'+str(i)+'.pcap'+'_Flow.csv'
    print(testdf)

    df=pd.read_csv(testdf)
    nan_list = df.isnull().sum().tolist()  # 把每一列的空值个数加起来
    print(nan_list)
    print(sum(nan_list))
    # 无穷值排查
    inf_list = np.isinf(df.drop(['Flow ID', 'Src IP', 'Dst IP', 'Timestamp','Label'], axis=1)).sum().tolist()  # 把每一列的无穷值个数加起来
    print(inf_list)
    print(sum(inf_list))
    # 删除空行，无穷值
    df = df.replace([np.inf, -np.inf], np.nan).dropna(axis=0)
    inf_list = np.isinf(df.drop(['Flow ID', 'Src IP', 'Dst IP', 'Timestamp','Label'], axis=1)).sum().tolist()
    print(sum(inf_list))

    X_test = df[features]
    Y_cart = model_cart.predict(X_test)
    Y_id3 = model_id3.predict(X_test)
    Y = []
    for a in range(0, X_test.shape[0]):
        if Y_id3[a] == 0 or Y_cart[a] == 0:
            Y.append(0)
        else:
            Y.append(Y_cart[a])
    flowID=[]
    rule=''
    for a in range(0,X_test.shape[0]):
        if Y[a] == 1:
            flowID.append(df['Flow ID'][a])
            mark=df.iloc[a:a+1,:]
            mark.to_csv('result.csv',mode='a')
    # filename='selection'+str(i)+'.txt'
    # f=open(filename,'w')
    # f.write(str(flowID))
    # f.close()
    # print(filename)
    for a in flowID:
        mark=a.split('-')
        rule=rule+'(ip.addr=='+mark[0]+' && ip.addr=='+mark[1]+' && tcp.port=='+mark[2]+' && tcp.port=='+mark[3]+') || '
    if flowID:
        rule = rule[:-4]
        cmd_select = 'sudo tshark -r number' + str(i) + '.pcap' + ' -Y' + ' "' + rule + '"' + ' -w' + ' selection' + str(i) + '.pcap'
        print(cmd_select)
        os.system(cmd_select)
        pkts_name='selection'+str(i)+'.pcap'
        new_name='detection'+str(i)+'.pcap'
        pkts=rdpcap(pkts_name)
        for pkt in pkts.res:
            pkt_load = pkt.getlayer('Raw')
            if re.search(match_str, str(pkt_load)):
                rename_cmd='mv '+pkts_name+' '+new_name
                os.system(rename_cmd)
                break
    cmd_delpcap = 'sudo rm number' + str(i) + '.pcap'
    print(cmd_delpcap)
    os.system(cmd_delpcap)
    cmd_delcsv = 'sudo rm csv/number' + str(i) + '.pcap' + '_Flow.csv'
    print(cmd_delcsv)
    os.system(cmd_delcsv)

i=1
while True:
    th=threading.Thread(target=os_cmd,args=(i,))
    th.start()
    i=i+1
    time.sleep(180)