Risk Assessment of Security Systems Based on Entropy Theory and Neyman-Pearson Criterion

被引:1
|
作者
Lv, Haitao [1 ]
Hu, Ruimin [2 ]
机构
[1] Wuhan Univ, Natl Engn Res Ctr Multimedia Software, Wuhan 430072, Peoples R China
[2] Wuhan Univ, Sch Comp, Wuhan 430072, Peoples R China
来源
2013 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCES AND APPLICATIONS (CSA) | 2013年
关键词
Security System; Risk Entropy; Neyman-Person Criterion; Security Network; Vulnerable Path;
D O I
10.1109/CSA.2013.8
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
For a security system, the risk assessment is an important metric to judge whether the protection effectiveness of a security system is good or not. In this paper, the security systems deployed in a guard field are regarded abstractly as a diagram of security network. Firstly a method about risk assessment based on entropy theory and Neyman-Pearson criterion is proposed. Secondly, the most vulnerable path formulation of a security network is described and a solution by utilizing the Dijkstra's shortest path algorithm is provided. The protection probability on the most vulnerable path is considered as the risk measure of a security network. Furthermore, we study the effects of some parameters on the risk and the breach protection probability and present simulations. Ultimately, we can gain insight about the risk of a security network.
引用
收藏
页码:1 / 5
页数:5
相关论文
共 50 条
  • [31] A reciprocity principle for the Neyman-Pearson theory of testing statistical hypotheses
    Court, LM
    ANNALS OF MATHEMATICAL STATISTICS, 1944, 15 : 326 - 327
  • [32] Stochastic Resonance Effect in Optimal Decision Solution Under Neyman-Pearson Criterion
    Yang, Ting
    Li, Yu
    Yang, Shiju
    Liu, Shujun
    CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2021, 40 (07) : 3286 - 3304
  • [33] Neyman-Pearson lemma based on intuitionistic fuzzy parameters
    Akbari, Mohammad Ghasem
    Hesamian, Gholamreza
    SOFT COMPUTING, 2019, 23 (14) : 5905 - 5911
  • [34] Noise enhanced hypothesis-testing according to restricted Neyman-Pearson criterion
    Bayram, Suat
    Gultekin, San
    Gezici, Sinan
    DIGITAL SIGNAL PROCESSING, 2014, 25 : 17 - 27
  • [35] Necessary conditions for optimum distributed sensor detectors under the Neyman-Pearson criterion
    Blum, RS
    IEEE TRANSACTIONS ON INFORMATION THEORY, 1996, 42 (03) : 990 - 994
  • [36] Reduced Complexity Optimal Hard Decision Fusion under Neyman-Pearson Criterion
    Nikhil, D.
    Mohammad, Fayazur Rahaman
    Mohammed, Zafar Ali Khan
    2018 26TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2018,
  • [37] New neural network realization algorithm for Neyman-Pearson criterion in hypothesis testing
    Zhang, Z.L.
    Sun, S.H.
    2001, Harbin Institute of Technology (33):
  • [38] ERROR-BOUNDS FOR PARALLEL DISTRIBUTED DETECTION UNDER THE NEYMAN-PEARSON CRITERION
    CHEN, PN
    PAPAMARCOU, A
    IEEE TRANSACTIONS ON INFORMATION THEORY, 1995, 41 (02) : 528 - 533
  • [39] Radar detection with the Neyman-Pearson criterion using supervised-learning-machines trained with the cross-entropy error
    Jarabo-Amores, Maria-Pilar
    de la Mata-Moya, David
    Gil-Pita, Roberto
    Rosa-Zurera, Manuel
    EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2013,