GT IoT Edu

About the Project

The exponential growth of IoT devices in institutions has brought new challenges in management, security, and usability. Our solution aims to democratize access to IoT technology in a secure and efficient way.

Current Challenges

Configuration Complexity

Bureaucratic and technical processes that hinder the adoption of IoT devices

Inadequate Security

Lack of standardized protocols for IoT devices on institutional networks

Dependence on IT

Users constantly rely on the technical staff for basic configurations

Our Solution

An intuitive platform that lets users register and manage their IoT devices on their own, with built-in security.

Sensors

Cameras

Smart

Audio/Video

Automation

Our Proposal

Simplify and secure the use of IoT devices in institutions.

Easy, Hassle-Free Registration

Users register their devices in seconds, without needing the IT team.

Intuitive interface

Automated validation

Automatic network configuration

Secure IoT Connectivity

Devices connected securely, with user accountability.

Automatic segmentation

Real-time monitoring

Built-in security policies

Automated Detection and Response

Signals prioritized by severity can trigger automatic blocking at the firewall, governed by security policies.

Consolidation of signals from multiple security sensors

Automatic blocking via firewall

Detection and Response Flow

IoT Traffic

Monitored
Security sensors

Suricata · Snort · Zeek
IoTEdu Core

Consolidation & prioritization
Firewall

Automatic blocking
Dashboard

Alerts

Multi-Sensor Orchestration

A unified pipeline to monitor, organize, and mitigate.

Suricata

Snort

Zeek

Consolidates signals from different detection engines to reduce false positives and speed up decision-making.

Normalization

Standardizes and organizes signals across different detection engines.

Consolidation

Groups signals by context and time to reduce noise and simplify analysis.

Mitigation

Automated triggers for actions (e.g., rules and blocks) when needed.

Traceability

Records evidence for continuous improvement of the pipeline.

Pitch Video

A quick overview of GT IoTEdu: the problem, the proposal, and how the project results connect and culminate in IoTEdu Core.

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IoTEdu at WRNP and SBRC 2026

We took the project to Praia do Forte (Bahia, Brazil), represented by Joner De Mello Assolin, Diego Kreutz, and Rodrigo Miani. We gave four presentations: two at WRNP 2026 (booth and main stage) and two at the SBRC 2026 Tools Session (Salão de Ferramentas). The highlights were IoT-ID (deterministic device fingerprinting) and IoT-Zoo (a testbed with more than 40 devices for reproducible, large-scale experiments). We came back with valuable feedback and new collaborations, some of them beyond Brazil!

View post on LinkedIn

Project Results

Explore the products and tools developed throughout the RNP Working Group.

Testbed

IoT-Zoo

A container-based framework for simulating heterogeneous IoT devices. It automates the deployment of multi-domain scenarios and traffic capture (PCAP) to support research, teaching, and solution validation.

IoT-Zoo Repository

Testbed

AttackZoo

A reproducible environment that integrates a containerized repository of attacks mapped to MITRE ATT&CK. It enables the traceable generation of network traffic datasets for cybersecurity research, teaching, and outreach.

AttackZoo Repository

Proof of Concept

Proof of Concept I

The first stage of the IoT device registration and validation flow: it identifies the device, records metadata, and paves the way for network provisioning and the enforcement of basic security controls.

See how it evolved into IoTEdu Core

Proof of Concept

Proof of Concept II

An evolution of the flow with built-in security: it connects security sensors to the environment and allows firewall policies to be triggered from collected evidence, while maintaining governance and traceability of actions.

See how it evolved into IoTEdu Core

Tool

IoT-ID Fingerprinting

A deterministic IoT device identification tool. It uses traffic analysis to produce stable, explainable identities without relying on probabilistic models or AI training.

IoT-ID Repository

Platform

IoTEdu Core (MVP)

The core that integrates registration with institutional security. It centralizes the collection of signals and alerts from security sensors and, based on them, enables responses via the firewall.

IoTEdu Core Repository

Public Datasets

Labeled network traffic datasets made openly available to the security and IoT research community.

Dataset · Attacks

GT-IoTEdu Attack Dataset

A labeled traffic dataset with 42 attack scenarios in a controlled environment, covering reconnaissance, network exploitation, web attacks, brute force, exfiltration, denial of service, and IoT. Generated by AttackZoo with MITRE ATT&CK mapping.

attack types

of capture

106.37 GB

of PCAPs

26.7 GB

final dataset

Access

Dataset · Benign Traffic

GT-IoTEdu IoT-Zoo Dataset

A packet-level benign traffic dataset captured on the IoT-Zoo testbed, with 43 heterogeneous device profiles across the Urban Observatory, Industrial, e-Health, and Smart Farming domains. It results from the synchronized merging of Scapy and Tshark captures.

device profiles

of capture

19 GB

of PCAPs

3.4 GB

final dataset

Access

Partnership & Support

A project funded by RNP and developed with the support of leading Brazilian higher education institutions.

Funding Network

Rede Nacional de Ensino e Pesquisa (Brazilian National Research and Educational Network)

A strategic partnership with RNP for the development and deployment of the GT IoTEdu platform, leveraging RNP's national network infrastructure to connect IoT devices securely and efficiently in educational institutions.