• DocumentCode
    3390585
  • Title

    A case study: Using architectural features to improve sophisticated denial-of-service attack detections

  • Author

    Tao, Ran ; Yang, Li ; Peng, Lu ; Li, Bin ; Cemerlic, Alma

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Louisiana State Univ., Baton Rouge, LA
  • fYear
    2009
  • fDate
    March 30 2009-April 2 2009
  • Firstpage
    13
  • Lastpage
    18
  • Abstract
    Application features such as port numbers are used by network-based intrusion detection systems (NIDSs) to detect attacks coming from networks. System calls and the operating system related information are used by host-based intrusion detection systems (HIDSs) to detect intrusions towards a host. However, the relationship between hardware architecture events and denial-of-service (DoS) attacks has not been well revealed. When increasingly sophisticated intrusions emerge, some attacks are able to bypass both the application and the operating system level feature monitors. Therefore, a more effective solution is required to enhance existing HIDSs. In this paper, we identify the following hardware architecture features: instruction count, cache miss, bus traffic and integrate them into a novel HIDS framework based on a modern statistical gradient boosting trees model. Through the integration of application, operating system and architecture level features, our proposed HIDS demonstrates a significant improvement of the detection rate in terms of sophisticated DoS intrusions.
  • Keywords
    security of data; statistical analysis; trees (mathematics); architecture level features; hardware architecture; network-based intrusion detection systems; operating system; sophisticated denial-of-service attack detections; statistical gradient boosting trees model; Application software; Boosting; Computer crime; Hardware; Intrusion detection; Operating systems; Radio access networks; TCPIP; Telecommunication traffic; Traffic control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Cyber Security, 2009. CICS '09. IEEE Symposium on
  • Conference_Location
    Nashville, TN
  • Print_ISBN
    978-1-4244-2769-7
  • Type

    conf

  • DOI
    10.1109/CICYBS.2009.4925084
  • Filename
    4925084