A New Approach of Botnet Activity Detection Model based on Time Periodic Analysis

Dandy Pramana Hostiadi, Tohari Ahmad, Waskitho Wibisono

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

Botnet is a serious and dangerous threat in a computer system. Bot infect a new computer to form bot network and produce an activity track record. Several previous studies have introduced a bot activity detection model by analyzing network flows traffic and performing static time segmentation. Inaccurate segmentation timing can eliminate bot activity chain and affect detection accuracy. This paper proposed a bot activity detection model by performing time segmentation using segment transition analysis. The proposed model identified multi-stage, analyzed the central node activity, and measured the similarity of the indicated activities in each segment. Last, the proposed model performs a chain trace to detect bot activity. Our goal is to perform an accurate detection of bot activity and tracking bot activity's communication chain by segment transition analysis. The results show that the proposed model can detect bot activity and bot activity's communication chain well with an accuracy of 97.93%.

Original languageEnglish
Title of host publicationCENIM 2020 - Proceeding
Subtitle of host publicationInternational Conference on Computer Engineering, Network, and Intelligent Multimedia 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages315-320
Number of pages6
ISBN (Electronic)9781728182834
DOIs
Publication statusPublished - 17 Nov 2020
Event2020 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2020 - Virtual, Surabaya, Indonesia
Duration: 17 Nov 202018 Nov 2020

Publication series

NameCENIM 2020 - Proceeding: International Conference on Computer Engineering, Network, and Intelligent Multimedia 2020

Conference

Conference2020 International Conference on Computer Engineering, Network, and Intelligent Multimedia, CENIM 2020
Country/TerritoryIndonesia
CityVirtual, Surabaya
Period17/11/2018/11/20

Keywords

  • Botnet
  • Intrusion Detection System
  • Periodic activity
  • multi-stage activity
  • network security

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