• DocumentCode
    3580938
  • Title

    Traffic anomaly detection in DDos flooding attack

  • Author

    Purwanto, Yudha ; Kuspriyanto ; Hendrawan ; Rahardjo, Budi

  • Author_Institution
    Bandung Insitute of Technol., Bandung, Indonesia
  • fYear
    2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Researches have been conducted to overcome Distributed Denial of Service (DDoS) flooding attack. Beside the use of signature based detection, anomaly based detection is also used to detect the attack. Several methods such as statistic, information theory, data mining and forecasting have been proposed. In several researches, they just focused to detect the traffic anomaly, but not to recognize the types of anomaly that were detected such as flashcrowd, types of botnet, types of DDoS, and prevention action. In this paper we categorize anomaly traffic detection system based on process and capability focus. Anomaly detection system process including traffic features, preprocessing, and detection process. Capability focus based on each main research problem to be solved, there are detectingonly anomaly, types of anomaly, and prevention system that include process to overcome the attack. At the end of paper, we provide overview of research direction and opportunities that may be done in future research.
  • Keywords
    data mining; security of data; statistical analysis; DDos flooding attack; anomaly based detection; data mining; distributed denial-of-service attack; forecasting method; information theory; signature based detection; statistic method; traffic anomaly detection; traffic detection process; traffic feature; traffic preprocessing; Conferences; Entropy; Feature extraction; Floods; Forecasting; Quality of service; Servers; DDoS; anomaly detection; botnet; flashcrowd; prevention;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Telecommunication Systems Services and Applications (TSSA), 2014 8th International Conference on
  • Type

    conf

  • DOI
    10.1109/TSSA.2014.7065953
  • Filename
    7065953