Game Analysis of Privacy Protection Based on Nash Equilibrium in Big Data Environment

Yuting Zhang
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Abstract

Big data analysis has brought convenience to all fields of human life. At the same time, the problem of privacy leakage follows. Protecting user's private data and preventing sensitive information disclosure become urgent problems. However, big data has the characteristics of large amount of data, diversification of types and sources and rapid growth, so the traditional privacy protection technology is more and more unsuitable. The traditional privacy protection mechanism protects the privacy of users, at the same time, it will inevitably reduce the data utility[1]. On the basis of differential privacy knowledge, based on the Nash equilibrium privacy protection mechanism, this paper constructs an interrelated differential privacy model, analyzes and evaluates the game model among multiple data publishers, and proves the correctness of the game analysis.
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大数据环境下基于纳什均衡的隐私保护博弈分析
大数据分析为人类生活的各个领域带来了便利。与此同时,隐私泄露问题也随之而来。保护用户隐私数据,防止敏感信息泄露成为亟待解决的问题。然而,大数据具有数据量大、类型和来源多样化、增长迅速等特点,传统的隐私保护技术越来越不适应。传统的隐私保护机制在保护用户隐私的同时,不可避免地会降低数据的效用[1]。本文在差分隐私知识的基础上,基于纳什均衡隐私保护机制,构建了一个相互关联的差分隐私模型,并对多个数据发布者之间的博弈模型进行了分析和评价,验证了博弈分析的正确性。
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