• DocumentCode
    3398805
  • Title

    Survey on data mining techniques to enhance intrusion detection

  • Author

    Denatious, Deepthy K. ; John, Anita

  • Author_Institution
    Dept. of Comput. Sci., Rajagiri Sch. of Eng. & Technol., Cochin, India
  • fYear
    2012
  • fDate
    10-12 Jan. 2012
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Nowadays, as information system plays critical part in the internet, the importance of secure networks is tremendously increased. Intrusion Detection System (IDS) is used to preserve the data integrity, confidentiality and system availability from attacks. Data mining is used to clean, classify and examine large amount of network data. Since a large volume of network traffic that requires processing, we use data mining techniques. Different Data Mining techniques such as clustering, classification and association rules are proving to be useful for analyzing network traffic. This paper presents the survey on data mining techniques applied on intrusion detection systems for the effective identification of both known and unknown patterns of attacks, thereby helping the users to develop secure information systems.
  • Keywords
    Internet; data integrity; data mining; information systems; pattern classification; pattern clustering; reliability; security of data; Internet; association rules; clustering; data confidentiality preservation; data integrity preservation; data mining technique; information system; intrusion detection system; network data classification; network data cleaning; network data examination; network security; network traffic analysis; system availability preservation; Algorithm design and analysis; Association rules; Clustering algorithms; Computers; Data models; Intrusion detection; association rule; classification; clustering; data mining; intrusion detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Communication and Informatics (ICCCI), 2012 International Conference on
  • Conference_Location
    Coimbatore
  • Print_ISBN
    978-1-4577-1580-8
  • Type

    conf

  • DOI
    10.1109/ICCCI.2012.6158822
  • Filename
    6158822