IDEAS home Printed from
   My bibliography  Save this article

Web Applications Vulnerability Management using a Quantitative Stochastic Risk Modeling Method


  • Sergiu SECHEL



The aim of this research is to propose a quantitative risk modeling method that reduces the guess work and uncertainty from the vulnerability and risk assessment activities of web based applications while providing users the flexibility to assess risk according to their risk appetite and tolerance with a high degree of assurance. The research method is based on the research done by the OWASP Foundation on this subject but their risk rating methodology needed de-bugging and updates in different in key areas that are presented in this paper. The modified risk modeling method uses Monte Carlo simulations to model risk characteristics that can’t be determined without guess work and it was tested in vulnerability assessment activities on real production systems and in theory by assigning discrete uniform assumptions to all risk charac-teristics (risk attributes) and evaluate the results after 1.5 million rounds of Monte Carlo simu-lations.

Suggested Citation

  • Sergiu SECHEL, 2017. "Web Applications Vulnerability Management using a Quantitative Stochastic Risk Modeling Method," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 21(3), pages 16-30.
  • Handle: RePEc:aes:infoec:v:21:y:2017:i:3:p:16-30

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Andrew X. Li, 2015. "State-Society Synergy and Export Sophistication," Economics and Politics, Wiley Blackwell, vol. 27(3), pages 433-458, November.
    2. Marian STOICA & Bogdan GHILIC-MICU & Marinela MIRCEA & Cristian USCATU, 2016. "Analyzing Agile Development – from Waterfall Style to Scrumban," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 20(4), pages 5-14.
    Full references (including those not matched with items on IDEAS)


    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:aes:infoec:v:21:y:2017:i:3:p:16-30. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Paul Pocatilu). General contact details of provider: .

    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 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.