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master's thesis
Analiza i detekcija zlonamjernog Javascript koda
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:452696
Pušelj, Dora
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Pušelj, D. (2021). Analiza i detekcija zlonamjernog Javascript koda (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:452696

Pušelj, Dora. "Analiza i detekcija zlonamjernog Javascript koda." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:452696

Pušelj, Dora. "Analiza i detekcija zlonamjernog Javascript koda." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:452696

Pušelj, D. (2021). 'Analiza i detekcija zlonamjernog Javascript koda', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 14 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:452696

Pušelj D. Analiza i detekcija zlonamjernog Javascript koda [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 November 14] Available at: https://urn.nsk.hr/urn:nbn:hr:168:452696

D. Pušelj, "Analiza i detekcija zlonamjernog Javascript koda", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:452696

Metadata
TitleAnaliza i detekcija zlonamjernog Javascript koda
Title (english)Analysis and detection of malicious Javascript code
AuthorDora Pušelj
MentorMarin Vuković (mentor)
Committee memberMarin Vuković (predsjednik povjerenstva)
Committee memberMiljenko Mikuc (član povjerenstva)
Committee memberMario Kušek (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-09, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Kako je Internet postao važan dio naše svakodnevice, tako su i razni napadi putem njega postali sve ćešći. Jedan od izvora takvih napada je upravo JavaScript kod. U ovome radu pokušava se detektirati takav zlonamjerni JavaScript kod tehnikama strojnog učenja. Iz JavaScript koda izgradi se apstraktno sintaksno stablo iz kojeg se pomoću DFS algoritma dobiju sekvence sintaktičkih jedinica. Zatim se koristi Word2Vec model kako bi se dobila numerička reprezentacija tih sintaktičkih jedinica. Učeni su modeli unaprijedna slojevita neuronska mreža, LSTM te BiLSTM te je pokazano kako BiLSTM daje najbolje rezultate.
Abstract (english)
As the Internet has become an important part of our everyday lives, the attacks by its means became more pervasive too. One of the sources of such attacks is JavaScript. In this thesis, a model for detecting malicious JavaScript is proposed. An AST tree is built from JavaScript source code and converted to a sequence of syntactic units by a depth-first search algorithm. Moreover, a Word2Vec model is used to obtain a numeric representation of the syntactic units. Three models are trained: feed-forward neural network, LSTM, and BiLSTM. The BiLSTM model turned out to give the best results.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:452696
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 on2023-01-13 13:37:09