Detail publikace

Detecting DoH-Based Data Exfiltration: FluBot Malware Case Study

RADER, R. JEŘÁBEK, K. RYŠAVÝ, O.

Originální název

Detecting DoH-Based Data Exfiltration: FluBot Malware Case Study

Typ

článek ve sborníku mimo WoS a Scopus

Jazyk

angličtina

Originální abstrakt

This paper presents a novel approach for detecting the FluBot malware, an advanced Android banking Trojan that has been observed in active attacks in 2021 and 2022. The proposed method uses a two-layer detection mechanism to identify FluBot network connections. In the first layer, a machine learning algorithm is used to detect DNS-over-HTTPS (DoH) within Netflow records. The second layer uses a modified version of an existing domain generation algorithm (DGA) detection algorithm to target the DoH connections associated with the FluBot malware specifically. To evaluate the effectiveness of this approach, we used a dataset consisting of FluBot network traffic captured in a controlled sandbox environment. The preliminary results show that our DoH classifier achieves high accuracy and detection rates in identifying instances of FluBot malware, while maintaining a low false positive rate.

Klíčová slova

DoH detection, malware detection, computer communication analysis, packet classification

Autoři

RADER, R.; JEŘÁBEK, K.; RYŠAVÝ, O.

Vydáno

12. 5. 2023

Nakladatel

IEEE Computer Society

Místo

Daytona Beach

ISBN

979-8-3503-0074-1

Kniha

IEEE 48th Conference on Local Computer Networks (LCN)

Strany od

50

Strany do

54

Strany počet

4

URL

https://www.fit.vut.cz/research/publication/13007/

BibTex

@inproceedings{BUT184570,
  author="Roman {Rader} and Kamil {Jeřábek} and Ondřej {Ryšavý}",
  title="Detecting DoH-Based Data Exfiltration: FluBot Malware Case Study",
  booktitle="IEEE 48th Conference on Local Computer Networks (LCN)",
  year="2023",
  pages="50--54",
  publisher="IEEE Computer Society",
  address="Daytona Beach",
  doi="10.1109/LCN58197.2023.10223341",
  isbn="979-8-3503-0074-1",
  url="https://www.fit.vut.cz/research/publication/13007/"
}

Dokumenty

Detecting_DoH-Based_Data_Exfiltration_FluBot_Malware_Case_Study.pdf
1570900880 paper.pdf