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import numpy as np
from scapy.all import rdpcap, IP, TCP, UDP, IPv6
import os
from collections import defaultdict
import statistics
def safe_div(x, y):
return x / y if y != 0 else 0
def calculate_stats(values):
if not values:
return 0, 0, 0, 0
return min(values), max(values), statistics.mean(values), statistics.stdev(values) if len(values) > 1 else 0
def convert_pcap_to_csv(pcap_file_path):
"""
Convert a PCAP file to a Pandas DataFrame with CIC-IDS-2017 like features using Scapy.
"""
try:
# Read PCAP file
packets = rdpcap(pcap_file_path)
flows = defaultdict(lambda: {
"src_ip": None, "dst_ip": None, "src_port": 0, "dst_port": 0, "protocol": 0,
"timestamps": [], "fwd_timestamps": [], "bwd_timestamps": [],
"fwd_pkt_lens": [], "bwd_pkt_lens": [], "all_pkt_lens": [],
"fwd_header_lens": [], "bwd_header_lens": [],
"flags": {"FIN": 0, "SYN": 0, "RST": 0, "PSH": 0, "ACK": 0, "URG": 0, "CWR": 0, "ECE": 0},
"fwd_flags": {"PSH": 0, "URG": 0},
"init_fwd_win": 0, "init_bwd_win": 0,
"fwd_act_data_pkts": 0, "fwd_seg_size_min": 0
})
for pkt in packets:
if IP in pkt:
src_ip = pkt[IP].src
dst_ip = pkt[IP].dst
proto = pkt[IP].proto
header_len = pkt[IP].ihl * 4
elif IPv6 in pkt:
src_ip = pkt[IPv6].src
dst_ip = pkt[IPv6].dst
proto = pkt[IPv6].nh
header_len = 40 # Fixed for IPv6
else:
continue
src_port = 0
dst_port = 0
payload_len = len(pkt.payload)
if TCP in pkt:
src_port = pkt[TCP].sport
dst_port = pkt[TCP].dport
flags = pkt[TCP].flags
window = pkt[TCP].window
elif UDP in pkt:
src_port = pkt[UDP].sport
dst_port = pkt[UDP].dport
flags = None
window = 0
else:
continue
# Flow Key (5-tuple)
key = (src_ip, dst_ip, src_port, dst_port, proto)
rev_key = (dst_ip, src_ip, dst_port, src_port, proto)
if key in flows:
flow = flows[key]
direction = "fwd"
elif rev_key in flows:
flow = flows[rev_key]
direction = "bwd"
else:
flow = flows[key]
flow["src_ip"] = src_ip
flow["dst_ip"] = dst_ip
flow["src_port"] = src_port
flow["dst_port"] = dst_port
flow["protocol"] = proto
direction = "fwd"
timestamp = float(pkt.time)
flow["timestamps"].append(timestamp)
flow["all_pkt_lens"].append(payload_len)
if direction == "fwd":
flow["fwd_timestamps"].append(timestamp)
flow["fwd_pkt_lens"].append(payload_len)
flow["fwd_header_lens"].append(header_len)
if TCP in pkt:
if flow["init_fwd_win"] == 0: flow["init_fwd_win"] = window
if payload_len > 0: flow["fwd_act_data_pkts"] += 1
flow["fwd_seg_size_min"] = header_len # Approximation
else:
flow["bwd_timestamps"].append(timestamp)
flow["bwd_pkt_lens"].append(payload_len)
flow["bwd_header_lens"].append(header_len)
if TCP in pkt:
if flow["init_bwd_win"] == 0: flow["init_bwd_win"] = window
if TCP in pkt and flags:
if 'F' in flags: flow["flags"]["FIN"] += 1
if 'S' in flags: flow["flags"]["SYN"] += 1
if 'R' in flags: flow["flags"]["RST"] += 1
if 'P' in flags:
flow["flags"]["PSH"] += 1
if direction == "fwd": flow["fwd_flags"]["PSH"] += 1
if 'A' in flags: flow["flags"]["ACK"] += 1
if 'U' in flags:
flow["flags"]["URG"] += 1
if direction == "fwd": flow["fwd_flags"]["URG"] += 1
if 'C' in flags: flow["flags"]["CWR"] += 1
if 'E' in flags: flow["flags"]["ECE"] += 1
# Process flows into features
rows = []
for flow in flows.values():
# Basic Stats
total_fwd_pkts = len(flow["fwd_pkt_lens"])
total_bwd_pkts = len(flow["bwd_pkt_lens"])
total_fwd_len = sum(flow["fwd_pkt_lens"])
total_bwd_len = sum(flow["bwd_pkt_lens"])
fwd_min, fwd_max, fwd_mean, fwd_std = calculate_stats(flow["fwd_pkt_lens"])
bwd_min, bwd_max, bwd_mean, bwd_std = calculate_stats(flow["bwd_pkt_lens"])
pkt_min, pkt_max, pkt_mean, pkt_std = calculate_stats(flow["all_pkt_lens"])
# Time Stats
duration = max(flow["timestamps"]) - min(flow["timestamps"]) if flow["timestamps"] else 0
if duration == 0: duration = 1e-6 # Avoid division by zero
flow_bytes_s = (total_fwd_len + total_bwd_len) / duration
flow_pkts_s = (total_fwd_pkts + total_bwd_pkts) / duration
fwd_pkts_s = total_fwd_pkts / duration
bwd_pkts_s = total_bwd_pkts / duration
# IAT Stats
flow_iats = [t2 - t1 for t1, t2 in zip(flow["timestamps"][:-1], flow["timestamps"][1:])]
fwd_iats = [t2 - t1 for t1, t2 in zip(flow["fwd_timestamps"][:-1], flow["fwd_timestamps"][1:])]
bwd_iats = [t2 - t1 for t1, t2 in zip(flow["bwd_timestamps"][:-1], flow["bwd_timestamps"][1:])]
flow_iat_min, flow_iat_max, flow_iat_mean, flow_iat_std = calculate_stats(flow_iats)
_, fwd_iat_max, _, fwd_iat_std = calculate_stats(fwd_iats)
_, bwd_iat_max, _, bwd_iat_std = calculate_stats(bwd_iats)
# Active/Idle (Simplified)
active_mean = 0
active_std = 0
active_max = 0
active_min = 0
idle_mean = 0
idle_std = 0
idle_max = 0
idle_min = 0
if flow_iats:
idle_threshold = 5.0 # seconds
idles = [iat for iat in flow_iats if iat > idle_threshold]
actives = [iat for iat in flow_iats if iat <= idle_threshold]
if idles:
idle_min, idle_max, idle_mean, idle_std = calculate_stats(idles)
if actives:
active_min, active_max, active_mean, active_std = calculate_stats(actives)
row = {
"Protocol": flow["protocol"],
"Total Fwd Packets": total_fwd_pkts,
"Total Backward Packets": total_bwd_pkts,
"Fwd Packets Length Total": total_fwd_len,
"Bwd Packets Length Total": total_bwd_len,
"Fwd Packet Length Max": fwd_max,
"Fwd Packet Length Min": fwd_min,
"Fwd Packet Length Std": fwd_std,
"Bwd Packet Length Max": bwd_max,
"Bwd Packet Length Min": bwd_min,
"Bwd Packet Length Std": bwd_std,
"Flow Bytes/s": flow_bytes_s,
"Flow Packets/s": flow_pkts_s,
"Flow IAT Mean": flow_iat_mean,
"Flow IAT Std": flow_iat_std,
"Flow IAT Max": flow_iat_max,
"Fwd IAT Std": fwd_iat_std,
"Fwd IAT Max": fwd_iat_max,
"Bwd IAT Std": bwd_iat_std,
"Bwd IAT Max": bwd_iat_max,
"Fwd PSH Flags": flow["fwd_flags"]["PSH"],
"Fwd URG Flags": flow["fwd_flags"]["URG"],
"Fwd Header Length": sum(flow["fwd_header_lens"]),
"Bwd Header Length": sum(flow["bwd_header_lens"]),
"Fwd Packets/s": fwd_pkts_s,
"Bwd Packets/s": bwd_pkts_s,
"Packet Length Min": pkt_min,
"Packet Length Max": pkt_max,
"Packet Length Mean": pkt_mean,
"Packet Length Std": pkt_std,
"FIN Flag Count": flow["flags"]["FIN"],
"SYN Flag Count": flow["flags"]["SYN"],
"RST Flag Count": flow["flags"]["RST"],
"PSH Flag Count": flow["flags"]["PSH"],
"ACK Flag Count": flow["flags"]["ACK"],
"URG Flag Count": flow["flags"]["URG"],
"CWE Flag Count": flow["flags"]["CWR"],
"ECE Flag Count": flow["flags"]["ECE"],
"Down/Up Ratio": safe_div(total_bwd_pkts, total_fwd_pkts),
"Init Fwd Win Bytes": flow["init_fwd_win"],
"Init Bwd Win Bytes": flow["init_bwd_win"],
"Fwd Act Data Packets": flow["fwd_act_data_pkts"],
"Fwd Seg Size Min": flow["fwd_seg_size_min"],
"Active Mean": active_mean,
"Active Std": active_std,
"Active Max": active_max,
"Active Min": active_min,
"Idle Mean": idle_mean,
"Idle Std": idle_std,
"Idle Max": idle_max,
"Idle Min": idle_min,
"Attack_type": "Unknown",
"Attack_encode": 0,
"mapped_label": "Unknown",
"severity_raw": 0,
"severity": "Unknown"
}
rows.append(row)
df = pd.DataFrame(rows)
return df
except Exception as e:
print(f"Error converting PCAP: {e}")
# Return empty DataFrame with expected columns on error
return pd.DataFrame()
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