IDEAS home Printed from https://ideas.repec.org/a/igg/jiit00/v14y2018i3p56-82.html
   My bibliography  Save this article

An Agent Based Intelligent Dynamic Vulnerability Analysis Framework for Critical SQLIA Attacks: Intelligent SQLIA Vulnerability Analyzer Agent

Author

Listed:
  • Jeya Mala Dharmalingam

    (Thiagarajar College of Engineering, Madurai, India)

  • M Eswaran

    (Zoho Corporation, Chennai, India)

Abstract

This article describes how software vulnerability analysis and testing for web applications should detect not only the common attacks but also dynamic vulnerability attacks. These are the attacks such as structured query language injection attacks (SQLIAs) which will extract the most crucial user information from the targeted database. In this proposed approach, an intelligent agent namely intelligent vulnerability analyzer agent (IVA) is proposed in which the external attacks due to dynamic user inputs are identified using a heuristic-guided intelligent graph searching and then a pre and post condition based analysis is performed to identify the dynamic vulnerabilities. Further, the proposed approach is compared with some of the existing works based on the number of false positives and false negatives of attacks detection and confirmed that the proposed work is a novel and effective one in finding out SQLIAs.

Suggested Citation

  • Jeya Mala Dharmalingam & M Eswaran, 2018. "An Agent Based Intelligent Dynamic Vulnerability Analysis Framework for Critical SQLIA Attacks: Intelligent SQLIA Vulnerability Analyzer Agent," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 14(3), pages 56-82, July.
    • Handle: RePEc:igg:jiit00:v:14:y:2018:i:3:p:56-82
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJIIT.2018070104
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Juan Du & Hengqing Jing & Kim-Kwang Raymond Choo & Vijayan Sugumaran & Daniel Castro-Lacouture, 2020. "An Ontology and Multi-Agent Based Decision Support Framework for Prefabricated Component Supply Chain," Information Systems Frontiers, Springer, vol. 22(6), pages 1467-1485, December.
    2. Juan Du & Hengqing Jing & Kim-Kwang Raymond Choo & Vijayan Sugumaran & Daniel Castro-Lacouture, 0. "An Ontology and Multi-Agent Based Decision Support Framework for Prefabricated Component Supply Chain," Information Systems Frontiers, Springer, vol. 0, pages 1-19.

    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:jiit00:v:14:y:2018:i:3:p:56-82. 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.