Compositional Closure for Bayes Risk in Probabilistic Noninterference

被引:0
|
作者
McIver, Annabelle [1 ]
Meinicke, Larissa [1 ]
Morgan, Carroll [2 ]
机构
[1] Macquarie Univ, Dept Comp Sci, N Ryde, NSW 2109, Australia
[2] Univ New South Wales, Sch Comp Sci & Engn, Sydney, NSW 2052, Australia
基金
澳大利亚研究理事会;
关键词
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
We give a quantitative sequential model for noninterference security with probability (but not demonic choice), and a novel refinement order that we prove to be the greatest compositional relation consistent with an "elementary" order based on Bayes Risk. This compositional closure complements our earlier work defining refinement similarly for qualitative noninterference with demonic choice (but not probability). The Three-Judges Protocol illustrates our model's utility: with compositionality, the embedded sub-protocols can be treated in isolation.
引用
收藏
页码:223 / +
页数:3
相关论文
共 50 条
  • [31] Probabilistic compositional models: Solution of an equivalence problem
    Kratochvil, Vaclav
    INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 2013, 54 (05) : 590 - 601
  • [32] Compositional Semantics for Probabilistic Programs with Exact Conditioning
    Stein, Dario
    Staton, Sam
    2021 36TH ANNUAL ACM/IEEE SYMPOSIUM ON LOGIC IN COMPUTER SCIENCE (LICS), 2021,
  • [33] CLOSURE-PROPERTIES OF THE COMPOSITIONAL RULE OF INFERENCE
    HELLENDOORN, H
    FUZZY SETS AND SYSTEMS, 1990, 35 (02) : 163 - 183
  • [34] LIMITING RISK OF BAYES AND EMPIRICAL BAYES ESTIMATORS .1. BAYES CASE
    EFRON, B
    MORRIS, C
    JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1971, 66 (336) : 807 - 815
  • [35] ASYMPTOTIC-BEHAVIOR OF BAYES TESTS AND BAYES RISK
    JOHNSON, BR
    TRUAX, DR
    ANNALS OF STATISTICS, 1974, 2 (02): : 278 - 294
  • [36] The Bayes Tree: An Algorithmic Foundation for Probabilistic Robot Mapping
    Kaess, Michael
    Ila, Viorela
    Roberts, Richard
    Dellaert, Frank
    ALGORITHMIC FOUNDATIONS OF ROBOTICS IX, 2010, 68 : 157 - +
  • [37] Probabilistic Reconciliation of Hierarchical Forecast via Bayes' Rule
    Corani, Giorgio
    Azzimonti, Dario
    Augusto, Joao P. S. C.
    Zaffalon, Marco
    MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES, ECML PKDD 2020, PT III, 2021, 12459 : 211 - 226
  • [38] Enhancing Bayes' Probabilistic Decision Support with a Fuzzy Approach
    Christias, Panagiotis
    Mocanu, Mariana
    2019 22ND INTERNATIONAL CONFERENCE ON CONTROL SYSTEMS AND COMPUTER SCIENCE (CSCS), 2019, : 259 - 263
  • [39] PROBABILISTIC POTENTIOMETRIC SURFACE MAPPING - CLOSURE
    KULATILAKE, PHSW
    JOURNAL OF GEOTECHNICAL ENGINEERING-ASCE, 1991, 117 (09): : 1458 - 1458
  • [40] On the probabilistic closure of the loose unambiguous hierarchy
    Hirsch, Edward A.
    Sokolov, Dmitry
    INFORMATION PROCESSING LETTERS, 2015, 115 (09) : 725 - 730