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undergraduate thesis
Detekcija i analiza višestupanjskog malvera
2023. urn:nbn:hr:200:688676
Žagar, Matija
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Communications
Chair of Radiocommunications and Telecommunications

Cite this document

Žagar, M. (2023). Detekcija i analiza višestupanjskog malvera (Undergraduate thesis). Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek. Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:688676

Žagar, Matija. "Detekcija i analiza višestupanjskog malvera." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2023. https://urn.nsk.hr/urn:nbn:hr:200:688676

Žagar, Matija. "Detekcija i analiza višestupanjskog malvera." Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2023. https://urn.nsk.hr/urn:nbn:hr:200:688676

Žagar, M. (2023). 'Detekcija i analiza višestupanjskog malvera', Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 15 November 2024, https://urn.nsk.hr/urn:nbn:hr:200:688676

Žagar M. Detekcija i analiza višestupanjskog malvera [Undergraduate thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2023 [cited 2024 November 15] Available at: https://urn.nsk.hr/urn:nbn:hr:200:688676

M. Žagar, "Detekcija i analiza višestupanjskog malvera", Undergraduate thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:200:688676

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Metadata
TitleDetekcija i analiza višestupanjskog malvera
Title (english)Detection and analysis of multi-stage malware
AuthorMatija Žagar
MentorKrešimir Grgić (mentor)
Committee memberKrešimir Grgić (predsjednik povjerenstva)
Committee memberGoran Knežević (član povjerenstva)
Committee memberDenis Vranješ (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Communications)
(Chair of Radiocommunications and Telecommunications)
Osijek
Defense date and country2023-07-12, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Electrical Engineering
Telecommunications and Informatics
Abstract
Višerazinski malware predstavlja veliku prijetnju te zahtjeva veliki napor za razvoj sigurnosnih rješenja za suzbijanje njegovog širenja. U ovom radu opisan je višerazinski malware te Emotet malware koji je ovog tipa. Dan je pregled metoda i alata dva pristupa analizi i detekciji. Opisane su metode statičkog pristupa analizi koja obuhvaća analizu karakteristika izvršne datoteke bez izvršavanja. Razvijena su YARA detekcijska pravila za statičku detekciju Emotet malware-a koja se temelje na pronalasku karakterističnih slijedova znakova u binarnom zapisu datoteke. Dan je pregled tehnika dinamičke analize malware-a kao što su analiza API poziva i mrežne komunikacije. Opisani su alati korišteni za ponašajnu analizu i njihovo korištenje. Razvijeno je Sigma pravilo za otkrivanje Emotet-a na temelju procesnog stabla. Opisana su područja primjene te prednosti i nedostaci oba pristupa.
Abstract (english)
Multi-stage malware represents a large threat and requires substantial effort in developing security solutions for combating its spread. This paper describes multi-stage malware and Emotet malware, which falls into this category. An overview of methods and tools for two different approaches to analysis and detection is given. A static approach to malware analysis is described, which involves analysis of a binary file without execution. YARA detection rules based on string matching are developed for static detection of Emotet. Techniques for dynamic analysis of malware are discussed, such as the analysis of API calls and network communication. Tools used for behavioral analysis and their utilization is described. A Sigma rule for detecting Emotet based on the process creation tree is developed. The advantages and disadvantages of both approaches are discussed, along with their respective target applications.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:688676
Study programmeTitle: Undergraduate University Study Programme in Computer Engineering
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2023-09-05 10:34:08