Lightweight traffic monitoring and analysis using video compression techniques

Marat Zhanikeev, Yoshiaki Tanaka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Traffic analysis based only on IP address is a new research area where traffic anomalies can be detected by studying clusters of IP addresses extracted from traveling packets. Such analysis is normally spatial and needs IP addresses to be put in a multi-dimensional map. This paper proposes a novel method that converts such maps to 2-dimensional graphical form and applies video compression techniques to create MPEG-2 VBR movies where frames are individual snapshots of IP space in time. The paper proves that this combination is suitable for traffic monitoring and detection of DDOS attacks as well as large-scale traffic anomalies caused by social phenomena.

Original languageEnglish
Title of host publicationManagement Enabling the Future Internet for Changing Business and New Computing Services - 12th Asia-Pacific Network Operations and Management Symposium, APNOMS 2009, Proceedings
Pages92-101
Number of pages10
DOIs
Publication statusPublished - 2009
Event12th Asia-Pacific Network Operations and Management Symposium, APNOMS 2009 - Jeju, Korea, Republic of
Duration: 2009 Sep 232009 Sep 25

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5787 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th Asia-Pacific Network Operations and Management Symposium, APNOMS 2009
CountryKorea, Republic of
CityJeju
Period09/9/2309/9/25

Keywords

  • Anomaly detection
  • IP space
  • Traffic analysis
  • Traffic monitoring
  • Video compression

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Lightweight traffic monitoring and analysis using video compression techniques'. Together they form a unique fingerprint.

Cite this