• DocumentCode
    2196051
  • Title

    Quantifying Information Leakage for Fully Probabilistic Systems

  • Author

    Yunchuan, Guo ; Lihua, Yin ; Yuan, Zhou ; Binxing, Fang

  • Author_Institution
    Inst. of Comput. Technol., Chinese Acad. of Sci., Beijing, China
  • fYear
    2010
  • fDate
    June 29 2010-July 1 2010
  • Firstpage
    589
  • Lastpage
    595
  • Abstract
    Quantifying the improper leakage of confidential information is a great challenge. In this paper, we propose a method to quantify the information leakage for a fully probabilistic system. Our approach relies on α mutual information (αMI). In our analysis, system is modeled as a fully probabilistic automata; information leakage is identified by means of the weak probabilistic trace equivalence, and then measured via αMI. The accuracy of our approach is demonstrated by experiments.
  • Keywords
    data privacy; probabilistic automata; security of data; α mutual information; confidential information leakage; fully probabilistic automata; weak probabilistic trace equivalence; Accuracy; Automata; Communication channels; Computational modeling; Computers; Probabilistic logic; Information Leakage; Quantitative Measure; aMI;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Technology (CIT), 2010 IEEE 10th International Conference on
  • Conference_Location
    Bradford
  • Print_ISBN
    978-1-4244-7547-6
  • Type

    conf

  • DOI
    10.1109/CIT.2010.122
  • Filename
    5578124