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Counter Deception in Belief Functions Using Shapley Value Methodology

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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.

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Acknowledgements

The work is partially supported by the Fund of the National Natural Science Foundation of China (Grant No. 61903307), China Postdoctoral Science Foundation (Grant No. 2020M683575), the Chinese Universities Scientific Fund (Grant No. 2452018066), and the National College Students Innovation and Entrepreneurship Training Program (Grant No. S202010712135, No. S202010712019, No. X202010712364). We also thank the anonymous reviewers for their valuable suggestions and comments.

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Authors and Affiliations

  1. College of Information Engineering, Northwest A&F University, Yangling, 712100, Shaanxi, China

    Lingge Zhou, Huizi Cui, Chongru Huang, Bingyi Kang & Jianfeng Zhang

  2. Key Laboratory of Agricultural Internet of Things, Ministry of Agriculture and Rural Affairs, Yangling, 712100, Shaanxi, China

    Bingyi Kang

  3. Shaanxi Key Laboratory of Agricultural Information Perception and Intelligent Service, Yangling, 712100, Shaanxi, China

    Bingyi Kang

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  1. Lingge Zhou
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Correspondence to Bingyi Kang or Jianfeng Zhang.

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Zhou, L., Cui, H., Huang, C. et al. Counter Deception in Belief Functions Using Shapley Value Methodology. Int. J. Fuzzy Syst. 24, 340–354 (2022). https://doi.org/10.1007/s40815-021-01139-1

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