Open Access

ARTICLE

Sensitive Information Protection Model Based on Bayesian Game

Yuzhen Liu^1,2, Zhe Liu³, Xiaoliang Wang^1,2,*, Qing Yang⁴, Guocai Zuo⁵, Frank Jiang⁶

1 School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, 411201, China
2 Hunan Key Laboratory for Service computing and Novel Software Technology, Xiangtan, 411201, China
3 College of computer and information engineering, Hunan University of Technology and Business, Changsha, China
4 School of Computer Science and Information Engineering, Guangzhou Maritime University, Guangzhou, China
5 Hunan Software Vocational and Technical University, Xiangtan, China
6 School of Engineering and IT, University of New South Wales, NSW, Australia

* Corresponding Author: Xiaoliang Wang. Email:

Computers, Materials & Continua 2022, 73(1), 883-898. https://doi.org/10.32604/cmc.2022.029002

Received 22 February 2022; Accepted 06 April 2022; Issue published 18 May 2022

Abstract

A game measurement model considering the attacker's knowledge background is proposed based on the Bayesian game theory aiming at striking a balance between the protection of sensitive information and the quality of service. We quantified the sensitive level of information according to the user's personalized sensitive information protection needs. Based on the probability distribution of sensitive level and attacker's knowledge background type, the strategy combination of service provider and attacker was analyzed, and a game-based sensitive information protection model was constructed. Through the combination of strategies under Bayesian equilibrium, the information entropy was used to measure the leakage of sensitive information. Furthermore, in the paper the influence of the sensitive level of information and the attacker's knowledge background on the strategy of both sides of the game was considered comprehensively. Further on, the leakage of the user's sensitive information was measured. Finally, the feasibility of the model was described by experiments.

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Keywords

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