• DocumentCode
    1324099
  • Title

    Fuzzy Classification Metrics for Scanner Assessment and Vulnerability Reporting

  • Author

    Loh, Peter Kok Keong ; Subramanian, Deepak

  • Author_Institution
    Comput. Security Lab., Nanyang Technol. Univ., Singapore, Singapore
  • Volume
    5
  • Issue
    4
  • fYear
    2010
  • Firstpage
    613
  • Lastpage
    624
  • Abstract
    In information security, web application scanners detect and provide some diagnoses for specific vulnerabilities. However, scanner performance as well as the damage potential of different vulnerabilities varies. This undermines the development of effective remediation solutions and the reliable sharing of vulnerability information. This paper describes an approach based on soft computing technology for the development of metrics that are used to grade web application scanners and vulnerabilities so that scanner performance can be evaluated and confidence levels can be computed for vulnerability reports. These metrics help derive a level of assurance that will support security management decisions, enhance effective remediation efforts, and could serve as security tool design metrics.
  • Keywords
    Internet; fuzzy set theory; neural nets; pattern classification; security of data; software metrics; software reliability; Web application scanners; fuzzy classification metrics; information security; scanner assessment; security management decisions; security tool design metrics; soft computing technology; vulnerability reporting; Classification algorithms; Fuzzy logic; Intrusion detection; Measurement; Software; Confidence level; Fuzzy classifiers; scanner; vulnerability; web application;
  • fLanguage
    English
  • Journal_Title
    Information Forensics and Security, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1556-6013
  • Type

    jour

  • DOI
    10.1109/TIFS.2010.2075926
  • Filename
    5570991