There are 0 repository under kdd-dataset topic.
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
Cyber-attack classification in the network traffic database using NSL-KDD dataset
An Anomaly based Intrusion Detection System: A Robust Machine Learning Approach
Assess various ML algorithms on KDD99 network dataset then apply the best algorithm (Random Forest) using R.
A Tensorflow model to detect network intrusions in the KDD Cup 1999 data-set.
[Anomaly detection] refers to the process of identifying patterns in data that do not conform to expected behavior. This project aims to develop a machine learning model to predict and identify potential attacks in IoT networks, thus helping to secure these networks from malicious activities.
Project developed during Network Security class at Federal University of Rio de Janeiro on spring 2017