Mazzariello, Claudio (2008) Multiple classifier systems for network security from data collection to attack detection. [Tesi di dottorato] (Unpublished)


Download (4MB) | Preview
[error in script] [error in script]
Item Type: Tesi di dottorato
Lingua: English
Title: Multiple classifier systems for network security from data collection to attack detection
Mazzariello, ClaudioUNSPECIFIED
Date: 2008
Date Type: Publication
Number of Pages: 145
Institution: Università degli Studi di Napoli Federico II
Department: Informatica e sistemistica
Dottorato: Ingegneria informatica ed automatica
Ciclo di dottorato: 20
Coordinatore del Corso di dottorato:
Cordella, Luigi PietroUNSPECIFIED
Date: 2008
Number of Pages: 145
Uncontrolled Keywords: Network security
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-INF/05 - Sistemi di elaborazione delle informazioni
Date Deposited: 31 Jul 2008
Last Modified: 30 Apr 2014 19:28
DOI: 10.6092/UNINA/FEDOA/2066


Since the Internet started developing, hosts and provided services have always been targeted with attacks trying to disrupt them. Trends show that, throughout the years, the number of hosts, as well as the degree of dependency of the whole society on the services provided through the Internet, increased dramatically, whereas the skills and knowledge required to interfere with normal network operation, and eventually to abruptly interrupt it, decreased accordingly. This considerations urge the requirement for effective tools, aimed at granting security to Internet users. The need for systems capable of detecting attacks, and reacting in order to prevent them from occurring again, is nowadays undeniable. In this thesis we propose methods based on multiple classifier systems for intrusion detection. We use such systems for automated data collection, also taking privacy issues into account. Some approaches to traffic classification are presented too, together with a proposal for the practical deployment of multiple classifiers in a real network environment.


Downloads per month over past year

Actions (login required)

View Item View Item