Popular GitHub Repositories for Ddos

Anomaly Detection on Time-Evolving Streams in Real-time. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.

An attempt to detect and prevent DDoS attacks using reinforcement learning. The simulation was done using Mininet.

ddos attack detector using ML Algorithms

Real-time eBPF-powered network security monitor with AI-driven threat detection. Surfaces port scans, DDoS attacks, botnet activity, and anomalies at 100Gbps+ speeds with sub-microsecond latency (~150 million packets/sec).

Machine Learning Based - Intrusion Detection System

Computers & Security

This research proposed an Advanced DDoS Attack Detection System (ADADS) using a Hybrid Detection Model (HDM) and Continuous Learning Model (CLM) for dynamic adaptation to evolving attack patterns.

Framework for implementing Network Intrusion Detection Systems (NIDS) aimed at identifying anomalies in network flows using Federated Learning models.

This project utilizes LSTM-based network intrusion detection to improve cybersecurity, achieving high accuracy and low false positive rates.

Artificial Neural Network designed with Tensorflow that classifies UDP data set into DDoS data set and normal traffic data set.

Analyzing a dataset for benign and DDoS attacks, involving data exploration, supervised and unsupervised learning, and cluster explainability analysis.

A Cloudflare Worker that monitors security events and sends alerts with AI-powered analysis.

LSTM based model classifying network packets to predict DDoS

Predict the future of your network using the best time series ML model that fit with your traffic.

Distributed HTTP stress testing via Discord slash commands and GitHub Actions using Locust.

This repository presents a machine learning project for detecting and classifying cybersecurity threats in network traffic. It involves data preprocessing, feature engineering, and the implementation of various models to accurately identify both normal activity and multiple types of attacks such as DDoS, DoS, and MITM.

My Mantis Botnet Analytics - For Research Purposes