IDEAS home Printed from https://ideas.repec.org/a/igg/jeis00/v12y2016i1p59-84.html
   My bibliography  Save this article

Flow-Graph and Markovian Methods for Cyber Security Analysis

Author

Listed:
  • Kouroush Jenab

    (Faculty of College of Aeronautics, Embry-Riddle Aeronautical University, Daytona Beach, FL, USA)

  • Sam Khoury

    (Faculty of College of Business, Athens State University, Athens, AL, USA)

  • Kim LaFevor

    (Athens State University, Athens, AL, USA)

Abstract

A flow-graph depicts the interrelationships among cyber security and security threats/incidents (i.e., internal, external, and accidental). Using a flow-graph, the manner in which security threats may affect systems can be investigated. This paper reports analytical approaches to analyze time to security threats and probability of security threat occurrence. Considering embedded threat detection functions in a safe-guard unit, the proposed approaches use the flow-graph concept, and Markovian method to calculate time to security threat occurrence and its probability. The threat detection functions are featured by incident detection and recovery mechanisms. The results of this study can be used by all parties (public and private sector organizations, service providers, IT, and insurance companies) to better deal with cyber security issues with respect to utilizing technology, investment, and insurance. An illustrative example is demonstrated to present the application of the approach.

Suggested Citation

  • Kouroush Jenab & Sam Khoury & Kim LaFevor, 2016. "Flow-Graph and Markovian Methods for Cyber Security Analysis," International Journal of Enterprise Information Systems (IJEIS), IGI Global, vol. 12(1), pages 59-84, January.
    • Handle: RePEc:igg:jeis00:v:12:y:2016:i:1:p:59-84
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJEIS.2016010104
    Download Restriction: no
    ---><---

    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:jeis00:v:12:y:2016:i:1:p:59-84. 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.