Lab-C2DC - Laboratory of Command and Control and Cyber-security

AB-TRAP

This is a five-step framework for the development of intrusion detection systems (IDS) using machine learning (ML) considering model realization, and performance evaluation.

fl-unsup-nids

T800

cve-reported

This repository includes all CVE discovered in our frameworks.

nastyware

iplite-sbseg2022

wsensing2021

Classification of Denial of Service Attacks on Wi-Fi-based Unmanned Aerial Vehicle

aBFF-sbseg2022

dismiss-bsm-globecom2022

fl-ieee-vtc2023

ransomware-minifilter

t800-sbrc2022

Ferramenta de firewall e benchmark para IoT

telegram-bot

wain2021

The source code for reproductibility of WAIN 2021 paper: Improving detection of scanning attacks on heterogeneous networks with Federated Learning

fl-ids-globecom2022

hids-iscc2024

pinion

sbrc2024-csi

screen-sbseg-2023

Um protótito de implementação do nosso paper no SBSeg2023.

dismiss-bsm-sbseg2022

nastyware-analyser

ab-trap-icc-2024

A kitsune version targeted to Raspberry PI

anomaly-flow

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

BinclustRE

fl-bsm-vtc2023

flids-wsensing2022

Ensemble model for detecting DDoS attacks across multiple domains

sbrc2024-ebfa_bb

screen-comst

spidersense-globecom2024