Ứng dụng học máy trong việc phát hiện DGA Botnet

Historic archive of preserved botnet data

Free botnet threat intel

An accessible quiz app to practice for CS6262 final exam

IoT Botnet Traffic Analysis using Deep Learning and Federated Learning. Published research project from Kennesaw State University. Paper: https://digitalcommons.kennesaw.edu/cgi/viewcontent.cgi?article=1044&context=cs_etd

This project explores **ensemble learning and deep learning** methods to build a robust botnet detection system. The goal is to compare classical ML baselines, deep neural architectures (CNN, LSTM), and tuned models to evaluate how well they identify botnet traffic.

Trabajo de Fin de Máster sobre Detección de Botnets para el Máster en Internet de las Cosas de la UCM

🔍 Detect IoT botnets like Mirai using GraphSAGE to analyze device activity as graphs, identifying malicious behavior effectively.

IoTSage: IoT Botnet Detection with GraphSAGE – A Graph Neural Network (GNN) based framework for detecting Mirai IoT botnet attacks. Converts IoT traffic into temporal graphs and applies GraphSAGE for classification, with evaluation metrics and visualization dashboard.

A web application for botnet detection using Machine Learning - XGBoost, from the csv file containing network packet flows, captured using CICFlowMeter Tool.

Lightweight honeypot that gathers and recognizes UDP & TCP packets.

Implementation of a PCA-based method for botnet detection using the FLAGS detection algorithm.

These are series of projects I have undertaken so far

Application of Deep Learning to Detect Botnets in Network Traffic Using CTU-13 Dataset

This repository contains code used for experiments in my BSc final thesis, “Multi-class Classification of Botnet Detection by Active Learning.”

Network Sniffer 🌐 : Un analyseur de paquets en Python pour détecter les comportements suspects et les attaques sur les réseaux locaux.

combating the llm fomo, feeding the shiny object syndrome, for folly and partially for curiousity

Collection of scripts that utilize Twitter API for suspicious behavior analysis

Intrusion Detection of Network using Machine Learning with Python. Our software serves as a robust tool for analysing network traffic, evaluating its safety, and identifying potential threats such as DDoS, SSH, Web attacks, BotNet, Infiltration, and Heartbleed

Malware Detection using ML classification