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

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Tipologia del documento: Tesi di dottorato
Lingua: English
Titolo: Multiple classifier systems for network security from data collection to attack detection
Autori:
AutoreEmail
Mazzariello, Claudio[non definito]
Data: 2008
Tipo di data: Pubblicazione
Numero di pagine: 145
Istituzione: Università degli Studi di Napoli Federico II
Dipartimento: Informatica e sistemistica
Dottorato: Ingegneria informatica ed automatica
Ciclo di dottorato: 20
Coordinatore del Corso di dottorato:
nomeemail
Cordella, Luigi Pietro[non definito]
Tutor:
nomeemail
Sansone, Carlo[non definito]
Data: 2008
Numero di pagine: 145
Parole chiave: Network security
Settori scientifico-disciplinari del MIUR: Area 09 - Ingegneria industriale e dell'informazione > ING-INF/05 - Sistemi di elaborazione delle informazioni
Depositato il: 31 Lug 2008
Ultima modifica: 30 Apr 2014 19:28
URI: http://www.fedoa.unina.it/id/eprint/2066
DOI: 10.6092/UNINA/FEDOA/2066

Abstract

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.

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