M.I.D.A.S. : metrics identification of attack surfaces

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dc.contributor.advisor Zage, Wayne M.
dc.contributor.author Meek, Joshua A.
dc.date.accessioned 2012-05-31T15:46:01Z
dc.date.available 2012-05-31T15:46:01Z
dc.date.created 2012-05-05
dc.date.issued 2012-05-05
dc.identifier.uri http://cardinalscholar.bsu.edu/handle/123456789/195941
dc.description.abstract This thesis endeavors to determine the feasibility of design metrics as a predictor of attack surface size by finding a positive correlation between one or more design metrics and an application’s attack surface measurement. An attack surface is the set of ways in which an adversary can enter a system and potentially cause damage. For an experimental setting, six open-source java-based projects were analyzed. For each project, the attack surface is assessed using Microsoft’s Attack Surface Analyzer, which takes a snapshot of a system state before and after the installation of product(s) and displays the changes to a number of key elements of the Windows attack surface. A collection of design metrics was collected from each open-source project as well. The goal is to find a metric or set of metrics that predicted the attack surface changes identified by the Attack Surface Analyzer.
dc.description.sponsorship Department of Computer Science
dc.subject.lcsh Cyberterrorism -- Prevention.
dc.subject.lcsh Software measurement.
dc.subject.lcsh Computer security -- Design.
dc.subject.other Microsoft Attack Surface Analyzer.
dc.title M.I.D.A.S. : metrics identification of attack surfaces en_US
dc.title.alternative Metrics identification of attack surfaces
dc.description.degree Thesis (M.S.)
dc.identifier.cardcat-url http://liblink.bsu.edu/catkey/1670305

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  • Master's Theses [5318]
    Master's theses submitted to the Graduate School by Ball State University master's degree candidates in partial fulfillment of degree requirements.

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