Alessandro Bonifazi
User Behaviour Classification by means of Unsupervised Learning optimized by DNN.
Rel. Fulvio Giovanni Ottavio Risso. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2019
|
Preview |
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (5MB) | Preview |
Abstract
In the last years, Machine Learning has been enjoying a novel surge of use in applications and problems from different domains, leveraging its power and allowing automation in various situations. This is for sure because of the big increase in data availability, in better computational power and in the improvement of Machine Learning techniques. [...] Computer networking can also benefit from this technology [...]. The aim is to study how the users exchange information (and which kind of information) through the network and find out a solid methodology in order to cluster local area network (LAN) users that share similar behaviour, allowing to exploit this discovery for resource management and anomalous activities identification.
The main challenges of a developer that is going to face a problem of this kind are: - which dataset should be used to train the model; which are the most meaningful data features that needs to be extracted and how they should be represented; - which is the best machine learning approach to follow and finally which is the correct algorithm to exploit
Relatori
Anno Accademico
Tipo di pubblicazione
Numero di pagine
Corso di laurea
Classe di laurea
Ente in cotutela
Aziende collaboratrici
URI
![]() |
Modifica (riservato agli operatori) |
