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

The Journal of Engineering

Bin Liu¹  Shi Cheng⁴ 

[1] School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, People'School of Computer Science, Shaanxi Normal University, Xi'an 710062, People's Republic of China

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

DOI  :  10.1049/joe.2016.0373

学科分类：工程和技术（综合）

来源: IET

【 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】

CC BY