• DocumentCode
    1852748
  • Title

    Research on network security real-time risk assessment model

  • Author

    Chen, Gengyuan

  • Author_Institution
    Int. Sch., Beijing Univ. of Posts & Telecommun., Beijing, China
  • Volume
    2
  • fYear
    2010
  • fDate
    1-3 Aug. 2010
  • Abstract
    Information Security Risk Assessment is a means of providing decision-makers with information needed to understand the vulnerabilities and threats factors that can negatively influence operations and outcomes and make informed judgments concerning the extent of actions needed to reduce risk. The first is to improve the parameter learning algorithm of CTHMMs. We compare it to the previous using the following indicators: pattern recognition and error rate as well as algorithm complexity. Improved algorithm is a contribution to the Markov theory. Stochastic statistical model pertain to discrete event dynamic system has recently become a familiar tool in computer and network security research. The importance and significance is difficult to express with ordinary glossary.
  • Keywords
    Markov processes; discrete event systems; real-time systems; risk management; security of data; CTHMM; Markov theory; discrete event dynamic system; information security; network security real-time risk assessment model; parameter learning algorithm; Algorithm design and analysis; Data models; Hidden Markov models; Markov processes; Risk management; Security; Sensors; Real-Time Risk Assessment; States; network security;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electronics and Information Engineering (ICEIE), 2010 International Conference On
  • Conference_Location
    Kyoto
  • Print_ISBN
    978-1-4244-7679-4
  • Electronic_ISBN
    978-1-4244-7681-7
  • Type

    conf

  • DOI
    10.1109/ICEIE.2010.5559746
  • Filename
    5559746