kddcup.py

"""Kddcup Dataset"""

from typing import List
from functools import partial

import datasets

import pandas


VERSION = datasets.Version("1.0.0")

_ENCODING_DICS = {
	"class": {value: i
			  for i, value in enumerate(["normal.",
										"buffer_overflow.",
										"loadmodule.",
										"perl.",
										"neptune.",
										"smurf.",
										"guess_passwd.",
										"pod.",
										"teardrop.",
										"portsweep.",
										"ipsweep.",
										"land.",
										"ftp_write.",
										"back.",
										"imap.",
										"satan.",
										"phf.",
										"nmap.",
										"multihop.",
										"warezmaster.",
										"warezclient.",
										"spy.",
										"rootkit."])
	}
}
_BASE_FEATURE_NAMES = [
	"duration",
	"protocol_type",
	"service",
	"flag",
	"src_bytes",
	"dst_bytes",
	"land",
	"wrong_fragment",
	"urgent",
	"hot",
	"num_failed_logins",
	"logged_in",
	"num_compromised",
	"root_shell",
	"su_attempted",
	"num_root",
	"num_file_creations",
	"num_shells",
	"num_access_files",
	"num_outbound_cmds",
	"is_host_login",
	"is_guest_login",
	"count",
	"srv_count",
	"serror_rate",
	"srv_serror_rate",
	"rerror_rate",
	"srv_rerror_rate",
	"same_srv_rate",
	"diff_srv_rate",
	"srv_diff_host_rate",
	"dst_host_count",
	"dst_host_srv_count",
	"dst_host_same_srv_rate",
	"dst_host_diff_srv_rate",
	"dst_host_same_src_port_rate",
	"dst_host_srv_diff_host_rate",
	"dst_host_serror_rate",
	"dst_host_srv_serror_rate",
	"dst_host_rerror_rate",
	"dst_host_srv_rerror_rate",
	"class",
]

DESCRIPTION = "Kddcup dataset."
_HOMEPAGE = ""
_URLS = ("")
_CITATION = """"""

# Dataset info
urls_per_split = {
	"train": "https://huggingface.co/datasets/mstz/kddcup/resolve/main/kddcup.data"
}
features_types_per_config = {
	"kddcup": {
		"duration": datasets.Value("float64"),
		"protocol_type": datasets.Value("string"),
		"service": datasets.Value("string"),
		"flag": datasets.Value("string"),
		"src_bytes": datasets.Value("int64"),
		"dst_bytes": datasets.Value("int64"),
		"land": datasets.Value("int64"),
		"wrong_fragment": datasets.Value("int64"),
		"urgent": datasets.Value("int64"),
		"hot": datasets.Value("int64"),
		"num_failed_logins": datasets.Value("int64"),
		"logged_in": datasets.Value("int64"),
		"num_compromised": datasets.Value("int64"),
		"root_shell": datasets.Value("int64"),
		"su_attempted": datasets.Value("int64"),
		"num_root": datasets.Value("int64"),
		"num_file_creations": datasets.Value("int64"),
		"num_shells": datasets.Value("int64"),
		"num_access_files": datasets.Value("int64"),
		"num_outbound_cmds": datasets.Value("int64"),
		"is_host_login": datasets.Value("int64"),
		"is_guest_login": datasets.Value("int64"),
		"count": datasets.Value("int64"),
		"srv_count": datasets.Value("int64"),
		"serror_rate": datasets.Value("float64"),
		"srv_serror_rate": datasets.Value("float64"),
		"rerror_rate": datasets.Value("float64"),
		"srv_rerror_rate": datasets.Value("float64"),
		"same_srv_rate": datasets.Value("float64"),
		"diff_srv_rate": datasets.Value("float64"),
		"srv_diff_host_rate": datasets.Value("float64"),
		"dst_host_count": datasets.Value("int64"),
		"dst_host_srv_count": datasets.Value("int64"),
		"dst_host_same_srv_rate": datasets.Value("float64"),
		"dst_host_diff_srv_rate": datasets.Value("float64"),
		"dst_host_same_src_port_rate": datasets.Value("float64"),
		"dst_host_srv_diff_host_rate": datasets.Value("float64"),
		"dst_host_serror_rate": datasets.Value("float64"),
		"dst_host_srv_serror_rate": datasets.Value("float64"),
		"dst_host_rerror_rate": datasets.Value("float64"),
		"dst_host_srv_rerror_rate": datasets.Value("float64"),
		"class": datasets.ClassLabel(num_classes=23,
									 names=("normal.", "buffer_overflow.", "loadmodule.", "perl.", "neptune.",
									 		"smurf.", "guess_passwd.", "pod.", "teardrop.", "portsweep.",
											"ipsweep.", "land.", "ftp_write.", "back.", "imap.", "satan.",
											"phf.", "nmap.", "multihop.", "warezmaster.", "warezclient.",
											"spy.", "rootkit.")),
	}
}
features_per_config = {k: datasets.Features(features_types_per_config[k]) for k in features_types_per_config}


class KddcupConfig(datasets.BuilderConfig):
	def __init__(self, **kwargs):
		super(KddcupConfig, self).__init__(version=VERSION, **kwargs)
		self.features = features_per_config[kwargs["name"]]


class Kddcup(datasets.GeneratorBasedBuilder):
	# dataset versions
	DEFAULT_CONFIG = "kddcup"
	BUILDER_CONFIGS = [
		KddcupConfig(name="kddcup", description="Kddcup for multiclass classification.")		
	]


	def _info(self):
		info = datasets.DatasetInfo(description=DESCRIPTION, citation=_CITATION, homepage=_HOMEPAGE,
									features=features_per_config[self.config.name])

		return info
	
	def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
		downloads = dl_manager.download_and_extract(urls_per_split)

		return [
			datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloads["train"]}),
		]
	
	def _generate_examples(self, filepath: str):
		data = pandas.read_csv(filepath, header=None)
		data.columns = _BASE_FEATURE_NAMES
		data = self.preprocess(data)

		for row_id, row in data.iterrows():
			data_row = dict(row)

			yield row_id, data_row

	def preprocess(self, data: pandas.DataFrame) -> pandas.DataFrame:
		for feature in _ENCODING_DICS:
			encoding_function = partial(self.encode, feature)
			data.loc[:, feature] = data[feature].apply(encoding_function)
				
		return data[list(features_types_per_config[self.config.name].keys())]

	def encode(self, feature, value):
		if feature in _ENCODING_DICS:
			return _ENCODING_DICS[feature][value]
		raise ValueError(f"Unknown feature: {feature}")