Thesis Details

Real-Time Detection of Malware Campaigns

Master's Thesis Student: Holop Patrik Academic Year: 2020/2021 Supervisor: Zobal Lukáš, Ing.
Czech title
Detekce kampaní škodlivého softwaru v reálném čase
Language
English
Abstract

This thesis deals with a real-time detection of malware campaigns based on the available data of internal tools used in the Avast Software company. Its goal is to design and implement a system that obtains and processes messages representing incidents detected at clients. The system extracts and processes useful information and estimates if the threat data are related to an emerging or continuous malware campaign based on various criteria. The experimentation proves that campaign detection based on the carefully selected data and metrics is possible. The implemented system is integrated with other internal tools of the Avast Software company. This thesis also suggests steps for further improving the detection process.

Keywords

malware, campaign, antivirus, detection, real-time event processing, Avast Software

Department
Degree Programme
Information Technology and Artificial Intelligence, Specialization Cybersecurity
Files
Status
defended, grade A
Date
22 June 2021
Reviewer
Committee
Hanáček Petr, doc. Dr. Ing. (DITS FIT BUT), předseda
Drábek Vladimír, doc. Ing., CSc. (DCSY FIT BUT), člen
Drahanský Martin, prof. Ing., Dipl.-Ing., Ph.D. (DITS FIT BUT), člen
Holík Lukáš, doc. Mgr., Ph.D. (DITS FIT BUT), člen
Malinka Kamil, Mgr., Ph.D. (DITS FIT BUT), člen
Veselý Vladimír, Ing., Ph.D. (DIFS FIT BUT), člen
Citation
HOLOP, Patrik. Real-Time Detection of Malware Campaigns. Brno, 2021. Master's Thesis. Brno University of Technology, Faculty of Information Technology. 2021-06-22. Supervised by Zobal Lukáš. Available from: https://www.fit.vut.cz/study/thesis/23731/
BibTeX
@mastersthesis{FITMT23731,
    author = "Patrik Holop",
    type = "Master's thesis",
    title = "Real-Time Detection of Malware Campaigns",
    school = "Brno University of Technology, Faculty of Information Technology",
    year = 2021,
    location = "Brno, CZ",
    language = "english",
    url = "https://www.fit.vut.cz/study/thesis/23731/"
}
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