Electronics and Domotics
CyberFold – Manifold Domain Learning para Detección de Intrusión y Anomalías
Fecha de inicio:
16 Jan 2023
Fecha de finalización prevista:
31 Dec 2025
CyberFold develops new solutions for detecting cyberattacks using manifold learning techniques and low-dimensional latent spaces. The aim is to identify anomalous behaviour in IoT, industrial and network systems, improving accuracy and reducing false positives. It also proposes the creation of new algorithms and their integration into real environments.
Project web
Project web
Código de proyecto -
40524
Results to be achieved:
1
Creation of a workbench for Manifold Domain Learning (MDL) algorithms.
2
Practical applications in anomaly detection in IoT, anomalous traffic, and DoS attacks.
3
Reduction of false positives in IDS systems.
4
Reduction of false positives in IDS systems.
5
Implementation of dashboards for monitoring and transfer to industry.
6
High-impact scientific publications.
7
System testing in real environments.
Project partners
Proyectos relacionados
i-VITAL
The aim of the project is to create a new vital sign monitoring and accident detection system that is seamlessly...
SERENA
We are working on the development of a complete intelligent system for the evaluation and improvement of sleep, whose...
finalizado
PHARAON
The project aims to lay the foundations and unify the technological challenges that the ageing of the population will...
Descargar
At Cetem we will process your data to call you back. You can exercise your rights at info@cetem.com. More information in privacy policy.
