Traffic model using a novel sniffer that ensures the user data privacy

Autor: Espinal Albert, Estrada Rebeca, Monsalve Carlos
Jazyk: English<br />French
Rok vydání: 2019
Předmět:
Zdroj: MATEC Web of Conferences, Vol 292, p 03002 (2019)
Druh dokumentu: article
ISSN: 2261-236X
DOI: 10.1051/matecconf/201929203002
Popis: Nowadays, the traffic over the networks is changing because of new protocols, devices and applications. Therefore, it is necessary to analyze the impact over services and resources. Traffic Classification of network is a very important prerequisite for tasks such as traffic engineering and provisioning quality of service. In this paper, we analyze the variable packet size of the traffic in an university campus network through the collected data using a novel sniffer that ensures the user data privacy. We separate the collected data by type of traffic, protocols and applications. Finally, we estimate the traffic model that represents this traffic by means of a Poisson process and compute its associated numerical parameters.
Databáze: Directory of Open Access Journals