Dinamička detekcija mehanizama za sprečavanje analize zloćudnog koda

master's thesis

• Title (english): Dynamic Detection of Anti-Reverse Techniques to Prevent Malware Analysis
• Author: Igor Novković
• Mentor: Stjepan Groš (mentor)
• Committee member: Stjepan Groš (predsjednik povjerenstva)
• Committee member: Leonardo Jelenković (član povjerenstva)
• Committee member: Vlado Sruk (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2016-07-11, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Zlonamjerni programi veliki su problem današnjom informatickoj sigurnosti. Kako
bi se navedni programi mogli prepoznati i ukloniti potrebna je njihova detaljna analiza.
Analiza zlocudnog koda, koja je teška sama po sebi, otežana je mehanizmima za spre-
cavanje analize koda koji oduzimaju dragocjeno vrijeme tijekom analize. Tijekom
ovog diplomskog rada razvijen je sustav koji bi mogao pomoci u prepoznavanju na-
vedenih mehanizama te time ubrzati postupak analize zlocudnih kodova. U radu dan
je uvod u problematiku analize zlocudnih kodova, opisan je izgradeni
sustavi te su predstavljeni rezultati sustava.

Abstract (english)

Malicious programs are a big problem for today’s informatic security. To be able to
recognize and remove malicious programs it is necesseary to analyse them. Malware
analysis, which is hard by itself, is made even more difficult by various anti-debug
techniques which steel precious time during analysis. During this master’s thesis a
system has been designed and implemented which could help to shorten time needed
for malware analyis by recognizing anti-debug techniques. In this work intro to pro-
blem of malware analysis is given, designed system is described and it’s results are
represented.

• Keywords: analiza zloćudnog koda; reverzno inženjerstvo; strojno učenje; mehanizmi za sprečavanje analize koda
• Keywords (english): malware analysis; reverse engineering; machine learning; anti-debug techniques
• Language: croatian
• URN:NBN: urn:nbn:hr:168:007978
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2018-02-06 10:56:47