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Counter Deception in Belief Functions Using Shapley Value Methodology

Authors :
Huizi Cui
Jianfeng Zhang
Bingyi Kang
Lingge Zhou
Chongru Huang
Source :
International Journal of Fuzzy Systems. 24:340-354
Publication Year :
2021
Publisher :
Springer Science and Business Media LLC, 2021.

Abstract

Counter deception is one of the main content in data fusion. The existence of deceptive data may cause great hidden dangers to the generation of correct decisions. While among previous studies, whether evidence should aggregate is still virgin and may become a fascinating question. In this paper, a new counter deception model based on the Shapley value methodology is proposed, which provides a perspective for determining the weight of evidence. Then, we present that the distance of evidence is a kind of “marginal contribution” to the anomaly of the entire fusion system. Moreover, we also investigated the properties of the proposed method to judge whether there is deceptive data in the information fusion based on the cooperation benefits of all basic belief assignment (BBA) combinations. Several numerical examples and a classification application were used to illustrate the practicability and effectiveness of the proposed methodology.

Details

ISSN :
21993211 and 15622479
Volume :
24
Database :
OpenAIRE
Journal :
International Journal of Fuzzy Systems
Accession number :
edsair.doi...........dfee9a692c45a6a94bf32d9a866df965
Full Text :
https://doi.org/10.1007/s40815-021-01139-1