IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i5p1652-d148060.html
   My bibliography  Save this article

An Automated Vulnerability Detection and Remediation Method for Software Security

Author

Listed:
  • Jeesoo Jurn

    (Korea Internet & Security Agency, 9, Jinheung-gil, Naju-si, Jeollanam-do 58324, Korea)

  • Taeeun Kim

    (Korea Internet & Security Agency, 9, Jinheung-gil, Naju-si, Jeollanam-do 58324, Korea)

  • Hwankuk Kim

    (Korea Internet & Security Agency, 9, Jinheung-gil, Naju-si, Jeollanam-do 58324, Korea)

Abstract

As hacking techniques become more sophisticated, vulnerabilities have been gradually increasing. Between 2010 and 2015, around 80,000 vulnerabilities were newly registered in the CVE (Common Vulnerability Enumeration), and the number of vulnerabilities has continued to rise. While the number of vulnerabilities is increasing rapidly, the response to them relies on manual analysis, resulting in a slow response speed. It is necessary to develop techniques that can detect and patch vulnerabilities automatically. This paper introduces a trend of techniques and tools related to automated vulnerability detection and remediation. We propose an automated vulnerability detection method based on binary complexity analysis to prevent a zero-day attack. We also introduce an automatic patch generation method through PLT/GOT table modification to respond to zero-day vulnerabilities.

Suggested Citation

  • Jeesoo Jurn & Taeeun Kim & Hwankuk Kim, 2018. "An Automated Vulnerability Detection and Remediation Method for Software Security," Sustainability, MDPI, vol. 10(5), pages 1-12, May.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:5:p:1652-:d:148060
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/5/1652/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/10/5/1652/
    Download Restriction: no
    ---><---

    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:gam:jsusta:v:10:y:2018:i:5:p:1652-:d:148060. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.