• DocumentCode
    3455921
  • Title

    Security Data Mining in an Ontology for Vulnerability Management

  • Author

    Wang, Ju An ; Guo, Minzhe

  • Author_Institution
    Sch. of Comput. & Software Eng., Southern Polytech. State Univ., Marietta, GA, USA
  • fYear
    2009
  • fDate
    3-5 Aug. 2009
  • Firstpage
    597
  • Lastpage
    603
  • Abstract
    Information security is such a complex topic that the sheer scope and volume of available security data overwhelms security professionals and managers alike. This paper discusses the rationale of applying semantic technology to information security with a focus on software vulnerability management. With semantic technologies, we can describe the pattern of external threats and internal vulnerabilities formally and precisely. Based on this, we can make inference and make high-level decisions accordingly. We have constructed an ontology for security vulnerabilities, which defines the key concepts in vulnerability management and their relationships. We introduce the design and reasoning within the ontology with examples in vulnerability analysis and assessment. The result of this paper provides a promising pathway to making security automation successful through semantic technologies.
  • Keywords
    data mining; decision making; inference mechanisms; ontologies (artificial intelligence); security of data; high-level decision making; inference mechanism; information security automation; ontology reasoning; security data mining; semantic technology; software vulnerability management; Biology computing; Conference management; Data mining; Data security; Engineering management; Information security; Ontologies; Risk management; Software engineering; Technology management; Information security; Measurement; Ontology; Semantic technology; Software vulnerabilities;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics, Systems Biology and Intelligent Computing, 2009. IJCBS '09. International Joint Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-0-7695-3739-9
  • Type

    conf

  • DOI
    10.1109/IJCBS.2009.13
  • Filename
    5260472