State space model-based trust evaluation over wireless sensor networks: an iterative particle filter approach

The Journal of Engineering

Bin Liu¹  Shi Cheng² 

[1] Nanjing University of Posts and Telecommunications;Shaanxi Normal University;

关键词: telecommunication security;    computational complexity;    iterative methods;    state estimation;    nonlinear filters;    particle filtering (numerical methods);    wireless sensor networks;    state-space methods;    high-dimensional trust evaluation;    computational complexity;    IPF algorithm;    iterative PF;    particle filter;    state estimation;    component-wise iterative state inference;    nonlinear state filtering problem;    server node;    data transmission;    SSTM;    state space trust model;    wireless sensor networks;    state space model-based trust evaluation;   

DOI  :  10.1049/joe.2016.0373

来源: DOAJ

【 摘 要 】

In this study, the authors propose a state space modelling approach for trust evaluation in wireless sensor networks. In their state space trust model (SSTM), each sensor node is associated with a trust metric, which measures to what extent the data transmitted from this node would better be trusted by the server node. Given the SSTM, they translate the trust evaluation problem to be a non-linear state filtering problem. To estimate the state based on the SSTM, a component-wise iterative state inference procedure is proposed to work in tandem with the particle filter (PF), and thus the resulting algorithm is termed as iterative PF (IPF). The computational complexity of the IPF algorithm is theoretically linearly related with the dimension of the state. This property is desirable especially for high-dimensional trust evaluation and state filtering problems. The performance of the proposed algorithm is evaluated by both simulations and real data analysis.

【 授权许可】

Unknown