A Suricata based NDR distribution

Network Intrusion Detection KDDCup '99', NSL-KDD and UNSW-NB15

Scirius is a web application for Suricata ruleset management and threat hunting.

Machine Learning with the NSL-KDD dataset for Network Intrusion Detection

Machine Learning for Network Intrusion Detection & Misc Cyber Security Utilities

Network Intrusion Detection based on various machine learning and deep learning algorithms using UNSW-NB15 Dataset

Network Intrusion Detection System Project using Machine Learning with code and Documents

Network intrusions classification using algorithms such as Support Vector Machine (SVM), Decision Tree, Naive Baye, K-Nearest Neighbor (KNN), Logistic Regression and Random Forest.

Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web I/O System.

Payload-Byte is a tool for extracting and labeling packet capture (Pcap) files of modern network intrusion detection datasets.

Network Intrusion Detection System

Repository for IEEE CCNC'21 paper titled "Edge-Detect: Edge-centric Network Intrusion Detection using Deep Neural Network".

En este proyecto se evalúan y comparan diferentes técnicas de aprendizaje automático para la detección de intrusiones en red.

GNN4ID: A Toolset for Crafting Graph Neural Network-Based NIDS Datasets

Implemented a network intrusion detection system for a software defined network using Random Forest method for classification of port and flow statistics.

Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web I/O System. The deployed project link is as follows.

Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning, Recurrent Neural Network models, MERN web I/O System.

The Unified Multimodal NIDS Dataset Tool performs the standardization of network intrusion detection datasets by extracting comprehensive flow, payload, and contextual features from raw PCAP files, ensuring consistency across datasets and enhancing machine learning-driven threat detection and analysis.

No description provided.

Neural Network based Intrusion Detection System (NIDS) on Intrusion Detection Evaluation Dataset (CICIDS2017)

This project showcases a Network Intrusion Detection System (NIDS) designed to bolster cybersecurity defenses against evolving threats

The given information of network connection, model predicts if connection has some intrusion or not. Binary classification for good and bad type of the connection further converting to multi-class classification and most prominent is feature importance analysis.

Assess various ML algorithms on KDD99 network dataset then apply the best algorithm (Random Forest) using R.

Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web I/O System.

WHU毕业设计，基于欠采样-随机森林的入侵检测模型。A simple WHU graduation project. Thank you Wuhan University.

Official repository of the "Network Intrusion Datasets: A Survey, Limitations, and Recommendations" by Goldschmidt and Chudá, 2025.

Analyzes network traffic and tells whether the query is normal or a type of attack. 3 classifiers are built and tested: Naive Bayes, Decision Trees, Random Forests, Followed by a complete visualization of results

Network Intrusion Detection in an Adversarial setting

10 Latest Final Year Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials

Keysight NAS (IXIA) Cloud Demo Examples