IDEAS home Printed from https://ideas.repec.org/a/igg/jcac00/v7y2017i3p1-43.html
   My bibliography  Save this article

Detection, Avoidance, and Attack Pattern Mechanisms in Modern Web Application Vulnerabilities: Present and Future Challenges

Author

Listed:
  • Shashank Gupta

    (Department of Computer Engineering, National Institute of Technology Kurukshetra, India)

  • B. B. Gupta

    (Department of Computer Engineering, National Institute of Technology Kurukshetra, India)

Abstract

In this paper, we present comprehensive survey of secured web application by identifying numerous serious threats faced by several-related organizations. Based on this, we have summarized the statistics of all emerging web application vulnerabilities by referring several-linked vulnerabilities and their classifications like US-CERT, CVE, CWE, NVD, OWASP etc. In addition, we present a comprehensive survey of the emerging web application weaknesses and discuss how to avoid, detect and attack pattern mechanisms of all critical web threats. Moreover, a detailed comparison has also been presented for all emerging web application exposures corresponding to certain threat agents, which indicates the level of the threat for a recognized vulnerability. In addition, we discuss numerous precautions that can be taken while defining lifecycle of web applications with hacking tools and describe ways to launch & utilize safety procedures and regular security controls in a recursive manner.

Suggested Citation

  • Shashank Gupta & B. B. Gupta, 2017. "Detection, Avoidance, and Attack Pattern Mechanisms in Modern Web Application Vulnerabilities: Present and Future Challenges," International Journal of Cloud Applications and Computing (IJCAC), IGI Global, vol. 7(3), pages 1-43, July.
  • Handle: RePEc:igg:jcac00:v:7:y:2017:i:3:p:1-43
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJCAC.2017070101
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ankit Kumar Jain & B. B. Gupta, 2018. "Towards detection of phishing websites on client-side using machine learning based approach," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 68(4), pages 687-700, August.

    More about this item

    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:igg:jcac00:v:7:y:2017:i:3:p:1-43. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.