IDEAS home Printed from https://ideas.repec.org/a/jbh/ijsrcs/v2y2017i6idhcseit1726216.html

A Review on Intelligent Data Mining and Soft Computing Techniques for Effective Intrusion Detection

Author

Listed:
  • Suma S G
  • Ganapathy Sannasi

Abstract

The world of computer today is increasingly dependent on interconnections between computer systems. Internet usage is increasing rapidly that the security against real time attack is a major concern. An intrusion detection system is a key defensive mechanism against the network attacks. Various approaches to intrusion detection are being used currently. This paper discusses about the various feature selection and intelligent classification techniques that are used to detect intrusions effectively. In addition to this, intrusion detection systems based on intelligent soft computing techniques are also discussed. Finally, a new intrusion detection model based on artificial immune system and fuzzy rough set based feature selection is suggested for effective and dynamic intrusion detection.

Suggested Citation

  • Suma S G & Ganapathy Sannasi, 2017. "A Review on Intelligent Data Mining and Soft Computing Techniques for Effective Intrusion Detection," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 2(6), pages 805-814, December.
    • Handle: RePEc:jbh:ijsrcs:v2:y2017:i6:id:hcseit1726216
    Note: Article URL: https://ijsrcseit.com/CSEIT1726216
    as

    Download full text from publisher

    File URL: https://ijsrcseit.com/CSEIT1726216
    File Function: Article URL
    Download Restriction: no
    File URL: https://ijsrcseit.com/paper/CSEIT1726216.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:jbh:ijsrcs:v2:y2017:i6:id:hcseit1726216. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Pankaj Sharma (USA) (email available below). General contact details of provider: https://ijsrcseit.com/home .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.