• DocumentCode
    2276461
  • Title

    Ontology for Detection of Web Attacks

  • Author

    Khairkar, A.D. ; Kshirsagar, D.D. ; Kumar, Sudhakar

  • Author_Institution
    Dept. of IT, Bharati Vidyapeeth Coll. of Eng., Pune, India
  • fYear
    2013
  • fDate
    6-8 April 2013
  • Firstpage
    612
  • Lastpage
    615
  • Abstract
    Intrusion Detection System (IDS) must reliably detect malicious activity. The expansion of web application also exponentially increases cyber threats. Current survey shows that application layer is more vulnerable to web attacks. There are more than 75% of attacks are deployed at application layer and out of that 90% are vulnerable to attacks. In this paper, we address issues of existing IDS i.e. low false positive rate, low false negative rate and data overload. We discuss about use of semantic web in the Intrusion Detection Systems. This article presents a proposition of using Semantic Web and Ontology concepts to define an approach to analyze Security logs with the goal to identify possible security issues. It extracts semantic relations between computer attacks and intrusions in an Intrusion Detection System. Ontology provides to enable, reuse of domain knowledge and it is also easier to understand and update legacy data.
  • Keywords
    Internet; ontologies (artificial intelligence); security of data; semantic Web; Web application; Web attacks; application layer; computer attacks; domain knowledge; intrusion detection system; legacy data; malicious activity detection; ontology concepts; security issues; semantic Web; Conferences; Data mining; Feature extraction; Genetic algorithms; Intrusion detection; Ontologies; Attacks; Intrusion Detection System; Ontology security; Semantic security; Web attacks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communication Systems and Network Technologies (CSNT), 2013 International Conference on
  • Conference_Location
    Gwalior
  • Print_ISBN
    978-1-4673-5603-9
  • Type

    conf

  • DOI
    10.1109/CSNT.2013.131
  • Filename
    6524474