• DocumentCode
    2194518
  • Title

    The Design and Implementation of Host-Based Intrusion Detection System

  • Author

    Lin Ying ; Zhang Yan ; Ou Yang-jia

  • Author_Institution
    Sch. of Software, Yunnan Univ., Kunming, China
  • fYear
    2010
  • fDate
    2-4 April 2010
  • Firstpage
    595
  • Lastpage
    598
  • Abstract
    Intrusion detection is the process of identifying and responding to suspicious activities targeted at computing and communication resources, and it has become the mainstream of information assurance as the dramatic increase in the number of attacks. Intrusion detection system (IDS) monitors and collects data from a target system that should be protected, processes and correlates the gathered information, and initiates responses when evidence of an intrusion is detected. In this paper, we designed and implemented a host-based intrusion detection system, which combines two detection technologies, one is log file analysis technology and the other is BP neural network technology. Log file analysis is an approach of misuse detection, and BP neural network is an approach of anomaly detection. By combination of these two kinds of detection technologies, the HIDS that we have implemented can effectively improve the efficiency and accuracy of intrusion detection.
  • Keywords
    backpropagation; data analysis; neural nets; security of data; BP neural network; anomaly detection; backpropagation; host-based intrusion detection system; log file analysis; Computer displays; Computer security; Decoding; Information analysis; Information technology; Intrusion detection; Neural networks; Pattern matching; Protection; Telecommunication traffic; BP neural network; HIDS; Log analysis; OSSEC; intrusion detection; intrusion detection system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Technology and Security Informatics (IITSI), 2010 Third International Symposium on
  • Conference_Location
    Jinggangshan
  • Print_ISBN
    978-1-4244-6730-3
  • Electronic_ISBN
    978-1-4244-6743-3
  • Type

    conf

  • DOI
    10.1109/IITSI.2010.127
  • Filename
    5453694