skip to main content
10.1145/505202.505211acmconferencesArticle/Chapter ViewAbstractPublication PagesimcConference Proceedingsconference-collections
Article

Characteristics of network traffic flow anomalies

Published:01 November 2001Publication History
First page image

References

  1. 1.K. Claffy, G. Polyzos, and H.-W. Braun, "Internet traffic flow profiling," Tech. Rep. TR-CS93-328, University of California San Diego, November 1989.Google ScholarGoogle Scholar
  2. 2.D. Plonka, "Flowscan: A network traffic flow reporting and visualization tool," in Proceedings of the USENIX Fourteenth System Administration Conference LISA XIV, New Orleans, LA, December 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. 3.Cisco's 10s Netflow Feature, http:flwww.cisco.comiwrapipublicl732/netflow.Google ScholarGoogle Scholar
  4. 4.R. Cficeres, "Measurements of wide-area Internet traffic," Tech. Rep. UCB/CSD 89/550, Computer Science Department, University of California, Berkeley, 1989. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. 5.V. Paxson, Measurements and Analysis of End-to-End Internet Dynamics, Ph.D. thesis, University of California Berkeley, 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. 6.V. Paxson and S. Floyd, "Wide-area traffic: The failure of Poisson modeling," IEEE/ACM Transactions on Networking, vol. 3(3), pp. 226-244, June 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. 7.W. Willinger, M. Taqqu, R. Sherman, and D. Wilson, "Selfsimilarity through high-variability: Statistical analysis of Ethernet LAN traffic at the source level," IEEE/ACM Transactions on Networking, vol. 5, no. 1, pp. 71-86, February 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. 8.P. Abry and D. Veitch, "Wavelet analysis of long range dependent traffic," IEEE Transactions on Information Theory, vol. 44, no. 1, 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. 9.K. Claffy, Internet TrafJ;c Characterization, Ph.D. thesis, University of California, San Diego, 1994. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. 10.I. Katzela and M. Schwartz, "Schemes for fault identificaiton in communicaitons networks," IEEE/ACM Transactions on Networking, vol. 3(6), pp. 753-764, December 1995. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. 11.F. Feather, D. Siewiorek, and R. Maxion, "Fault detection in an ethernet network using anomaly signature matching," in Proceedings of ACM SIGCOMM '93, San Francisco, CA, September 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. 12.J. Brutlag, "Aberrant behavior detection in time series for network monitoring," in Proceedings of the USENIX Fourteenth System Administration Conference LISA XIV, New Orleans, LA, December 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. 13.C. Hood and C. Ji, "Proactive network fault detection," in Proceedings of IEEE INFOCOM '97, Kobe, Japan, April 1997. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. 14.J. Toelle and O. Niggemann, "Supporting intrusion detection by graph clustering and graph drawing," in Proceedings of Third International Workshop on Recent Advances in Intrusion Detection RAID 2000, Toulouse, France, October 2000.Google ScholarGoogle Scholar
  15. 15.K. Fox, R. Henning, J. Reed, and R. Simonian, "A neural network approach towards intrusion detection," Tech. Rep., Harris Corporation, July 1990.Google ScholarGoogle Scholar
  16. 16.N. Ye, "A markov chain model of temporal behavior for anomaly detection," in Workshop on Information Assurance and Security, West Point, NY, June 2000.Google ScholarGoogle Scholar
  17. 17.D. Moore, G. Voelker, and S. Savage, "Inferring intemet denial-ofservice activity," in Proceedings of 2001 USENIX Security Symposium, Washington, DC, August 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. 18.V. Paxson, "Bra: A system for detecting network intruders in real-time," Computer Networks, vol. 31, no. 23-24, pp. 2435- 2463, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. 19.R. Manajan, S. Bellovin, S. Floyd, V. Paxson, S. Shenker, and J. Ioannidis, "Controlling high bandwidth aggregates in the network," ACIRI Draft paper, February 2001.Google ScholarGoogle Scholar

Index Terms

  1. Characteristics of network traffic flow anomalies

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        IMW '01: Proceedings of the 1st ACM SIGCOMM Workshop on Internet measurement
        November 2001
        319 pages
        ISBN:1581134355
        DOI:10.1145/505202

        Copyright © 2001 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 1 November 2001

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • Article

        Acceptance Rates

        IMW '01 Paper Acceptance Rate29of80submissions,36%Overall Acceptance Rate29of80submissions,36%

        Upcoming Conference

        IMC '24
        ACM Internet Measurement Conference
        November 4 - 6, 2024
        Madrid , AA , Spain

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader