Banca de DEFESA: RIVALDO FERNANDES DE ALBUQUERQUE PEREIRA

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : RIVALDO FERNANDES DE ALBUQUERQUE PEREIRA
DATE: 29/11/2023
TIME: 09:00
LOCAL: remoto
TITLE:

An Anomaly Detection Architecture in SDN using computational intelligence

KEY WORDS:

SDN, Anomalie detection, Machine learning

PAGES: 79
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUMMARY:

Emerging technologies such as the Cloud, 5G, Internet of Things (IoT) and edge computing encompass controlling and networking millions of devices every day. Managing traditional networks with millions of devices is a complex task as it requires configuring data traffic routes on each device in the network. With it centralized network controller, Software-Defined Networking (SDN) can help simplify the configuration and management of a network with this many devices. Many studies have researched the use of different computational intelligence (CI) methods to detect anomalies in SDN, this work defines a framework to validate, promote and explain, using Explainable AI, any of these CI methods that best detects each of the different types of anomalies, and also define architecture based on hexagonal microservices and with a unique data model based on the application and information framework, Open Digital Architecture, from the TM Forum

COMMITTEE MEMBERS:
Presidente - 3139050 - ROGER KREUTZ IMMICH
Interno - 1644456 - UIRA KULESZA
Externo ao Programa - 1525670 - MARCOS CESAR MADRUGA ALVES PINHEIRO - UFRNExterno à Instituição - DOUGLAS D. J. DE MACEDO - UFSC