Detail publikace

Malicious Events Grouping via Behavior Based Darknet Traffic Flow Analysis

PANG, S. KOMOSNÝ, D. ZHU, L. ZHANG, R. SARRAFZADEH, A. BAN, T. INOUE, D.

Originální název

Malicious Events Grouping via Behavior Based Darknet Traffic Flow Analysis

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

This paper proposes a host behavior based darknet traffic decomposition approach to identifying groups of malicious events from massive historical darknet traffic. In this approach, we segment traffic flows from captured darknet data, distinguish scan from non-scan flows, and categorize scans according to scan width spreads. Consequently, event groups are appraised by applying the criterion that malicious events generated by the same attacker or malicious software should have similar average packet delay, AvgDly. We have applied the proposed approach to 12 months darknet traffic data for malicious events grouping. As a result, several large scale event groups are discovered on host behavior in the category of port scan, IP scan and hybrid scan, respectively.

Klíčová slova

Darknet traffic; Malicious events grouping; Port scan; IP scan; Hybrid scan; Packet delay distribution; Traffic flow analysis

Autoři

PANG, S.; KOMOSNÝ, D.; ZHU, L.; ZHANG, R.; SARRAFZADEH, A.; BAN, T.; INOUE, D.

Vydáno

13. 10. 2017

ISSN

0929-6212

Periodikum

WIRELESS PERSONAL COMMUNICATIONS

Ročník

96

Číslo

4

Stát

Nizozemsko

Strany od

5335

Strany do

5353

Strany počet

19

BibTex

@article{BUT141089,
  author="Shaoning {Pang} and Dan {Komosný} and Lei {ZHU} and Ruibin {ZHANG} and Abdolhossein {SARRAFZADEH} and Tao {Ban} and Daisuke {Inoue}",
  title="Malicious Events Grouping via Behavior Based Darknet Traffic Flow Analysis",
  journal="WIRELESS PERSONAL COMMUNICATIONS",
  year="2017",
  volume="96",
  number="4",
  pages="5335--5353",
  doi="10.1007/s11277-016-3744-4",
  issn="0929-6212"
}