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master's thesis
Otkrivanje uljeza u mrežnom prometu
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:156535
Žada, Frane
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Žada, F. (2024). Otkrivanje uljeza u mrežnom prometu (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:156535

Žada, Frane. "Otkrivanje uljeza u mrežnom prometu." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:156535

Žada, Frane. "Otkrivanje uljeza u mrežnom prometu." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:156535

Žada, F. (2024). 'Otkrivanje uljeza u mrežnom prometu', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 27 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:156535

Žada F. Otkrivanje uljeza u mrežnom prometu [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2024 December 27] Available at: https://urn.nsk.hr/urn:nbn:hr:168:156535

F. Žada, "Otkrivanje uljeza u mrežnom prometu", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:156535

Metadata
TitleOtkrivanje uljeza u mrežnom prometu
Title (english)Network traffic intrusion detection
AuthorFrane Žada
MentorMartina Antonić (mentor)
Committee memberMartina Antonić (predsjednik povjerenstva)
Committee memberKrešimir Pripužić (član povjerenstva)
Committee memberDragan Jevtić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-07-11, Croatia
Abstract
U okviru ovog rada istražuje se primjena metoda strojnog učenja u detekciji uljeza u mrežnom prometu s ciljem unapređenja sigurnosti informacijskih sustava. Kroz pregled relevantne literature, metodologiju istraživanja, implementaciju različitih modela strojnog učenja te analizu dobivenih rezultata, pruža se sveobuhvatan uvid u trenutne mogućnosti u detekciji uljeza. Rezultati ukazuju na izvanredan potencijal modela poput stabla odlučivanja u identifikaciji zlonamjernih aktivnosti, pružajući korisne smjernice za razvoj efikasnijih sustava za sigurnost mrežnih sustava.
Abstract (english)
The thesis explores the application of machine learning algorithms for network traffic intrusion detection with the aim of enhancing the security of information systems. Through a review of relevant literature, research methodology, implementation of various machine learning models, and analysis of the obtained results, a comprehensive insight into the current state of the art in intrusion detection is provided. The results indicate the outstanding potential of models, such as decision trees, in identifying malicious activities, offering valuable guidance for the development of more efficient systems for network security.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:156535
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2024-10-12 22:33:39