Network Intrusion Detection KDDCup '99', NSL-KDD and UNSW-NB15
Machine Learning with the NSL-KDD dataset for Network Intrusion Detection
Machine Learning for Network Intrusion Detection & Misc Cyber Security Utilities
Simple Implementation of Network Intrusion Detection System. KddCup'99 Data set is used for this project. kdd_cup_10_percent is used for training test. correct set is used for test. PCA is used for dimension reduction. SVM and KNN supervised algorithms are the classification algorithms of project. Accuracy : %83.5 For SVM , %80 For KNN
Feature coded UNSW_NB15 intrusion detection data.
Solutions to kdd99 dataset with Decision tree and Neural network by scikit-learn
修改谷歌提供的样例量子卷积神经网络模型，基于KDD99数据集进行训练，实现了网络攻击分类检测。
using machine-learning to detecte instruction
This repository contains a notebook implementing an autoencoder based approach for intrusion detection, the full documentation of the study will be available shortly.
Abnormal Traffic Identification Classifier based on Machine Learning. My code for undergraduate graduation design.
Cyber-attack classification in the network traffic database using NSL-KDD dataset
Analysis and preprocessing of the kdd cup 99 dataset using python and scikit-learn
Assess various ML algorithms on KDD99 network dataset then apply the best algorithm (Random Forest) using R.
COSC 490 Towson University
An Intrusion Detection System (IDS) implemented in Python, which utilizes machine learning techniques and the KDD Cup 1999 dataset to detect and classify network intrusions in real-time.
This is the strong baseline in final competition (KDD1999) of NTU Machine Learning 2016 Fall lectured by Hung-Yi Lee
ISSS610 Applied Machine Learning
Demo of SciKit ML algorithms using the kdd99 dataset
INTRUSION DETECTOR | ML
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