Network Intrusion Detection KDDCup '99', NSL-KDD and UNSW-NB15
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Updated
May 8, 2019 - Python
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
Feature coded UNSW_NB15 intrusion detection data.
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
Solutions to kdd99 dataset with Decision tree and Neural network by scikit-learn
This repository contains a notebook implementing an autoencoder based approach for intrusion detection, the full documentation of the study will be available shortly.
Analysis and preprocessing of the kdd cup 99 dataset using python and scikit-learn
using machine-learning to detecte instruction
Abnormal Traffic Identification Classifier based on Machine Learning. My code for undergraduate graduation design.
This is a classification model with five classes (normal, DOS, R2L, U2R,PROBING). Ignore the content features of TCP connection ( columns 10-22 of KDD Cup 99 dataset) when training the model to adapt the project that a kdd99 feature extractor
Assess various ML algorithms on KDD99 network dataset then apply the best algorithm (Random Forest) using R.
Demo of SciKit ML algorithms using the kdd99 dataset
ISSS610 Applied Machine Learning
An introductory course to pandas and 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。
A Tensorflow model to detect network intrusions in the KDD Cup 1999 data-set.
Cyber-attack classification in the network traffic database using NSL-KDD dataset
COSC 490 Towson University
Project developed during Network Security class at Federal University of Rio de Janeiro on spring 2017
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