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master's thesis
Detekcija anomalija u podacima s ciljem otkrivanja sigurnosnih incidenata
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. urn:nbn:hr:168:206797
Travančić, Robert
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Travančić, R. (2024). Detekcija anomalija u podacima s ciljem otkrivanja sigurnosnih incidenata (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:206797

Travančić, Robert. "Detekcija anomalija u podacima s ciljem otkrivanja sigurnosnih incidenata." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:206797

Travančić, Robert. "Detekcija anomalija u podacima s ciljem otkrivanja sigurnosnih incidenata." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2024. https://urn.nsk.hr/urn:nbn:hr:168:206797

Travančić, R. (2024). 'Detekcija anomalija u podacima s ciljem otkrivanja sigurnosnih incidenata', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 14 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:206797

Travančić R. Detekcija anomalija u podacima s ciljem otkrivanja sigurnosnih incidenata [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2024 [cited 2024 November 14] Available at: https://urn.nsk.hr/urn:nbn:hr:168:206797

R. Travančić, "Detekcija anomalija u podacima s ciljem otkrivanja sigurnosnih incidenata", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2024. Available at: https://urn.nsk.hr/urn:nbn:hr:168:206797

Metadata
TitleDetekcija anomalija u podacima s ciljem otkrivanja sigurnosnih incidenata
Title (english)Data anomaly detection for discovering cybersecurity incidents
AuthorRobert Travančić
MentorMarin Vuković (mentor)
Committee memberMarin Vuković (predsjednik povjerenstva)
Committee memberDragan Jevtić (član povjerenstva)
Committee memberMiljenko Mikuc (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2024-02-27, Croatia
Abstract
Detekcija anomalija aktivno je područje istraživanja s rastućom važnošću u modernom digitalnom dobu. Primjena detekcije anomalija proteže se kroz različite aspekte svijeta oko nas od financijskih sustava, medicine pa sve do industrije. U radu su istraženi različiti pristupi detekciji anomalija s opisanim prednostima i nedostatcima. Implementiran je sustav za detekciju anomalija zasnovan na algoritmu Isolation Forest. Performanse modela su uspoređene s modelima zasnovanim na algoritmima Local Outlier Factor i One-class Support Vector Machine na različitim skupovima podataka. Rad opisuje izazove koji proizlaze iz korištenja algoritma Isolation Forest te je predloženo potencijalno rješenje u obliku hibridnog modela koji koristi algoritme Autoenkoder i Isolation Forest.
Abstract (english)
Anomaly detection is an active area of research with growing importance in the modern digital age. The application of anomaly detection extends across various aspects of the world around us, from financial systems, medicine to various types of industries. In this work, various approaches to anomaly detection are explored, with described advantages and disadvantages. An anomaly detection system based on the Isolation Forest algorithm has been implemented. The performance of the model was compared with models based on the Local Outlier Factor and One-class Support Vector Machine algorithms on different datasets. The work describes challenges arising from the use of the Isolation Forest algorithm and proposes a potential solution in the form of a hybrid model that uses Autoencoder and Isolation Forest algorithms.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:206797
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 on2024-03-28 07:56:09