Differential Privacy Protection Algorithm Based on Zero Trust Architecture for Industrial Internet

Yuning Song, Liping Ding, Xuehua Liu, Mo Du
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引用次数: 1

Abstract

The Zero Trust Architecture is an important part of the industrial Internet security protection standard. When analyzing industrial data for enterprise-level or industry-level applications, differential privacy (DP) is an important technology for protecting user privacy. However, the centralized and local DP used widely nowadays are only applicable to the networks with fixed trust relationship and cannot cope with the dynamic security boundaries in Zero Trust Architecture. In this paper, we design a differential privacy scheme that can be applied to Zero Trust Architecture. It has a consistent privacy representation and the same noise mechanism in centralized and local DP scenarios, and can balance the strength of privacy protection and the flexibility of privacy mechanisms. We verify the algorithm in the experiment, that using maximum expectation estimation method it is able to obtain equal or even better result of the utility with the same level of security as traditional methods.
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基于零信任架构的工业互联网差分隐私保护算法
零信任架构是工业互联网安全防护标准的重要组成部分。在为企业级或工业级应用程序分析工业数据时,差分隐私(DP)是保护用户隐私的一项重要技术。然而,目前广泛使用的集中式DP和本地DP仅适用于具有固定信任关系的网络,无法应对零信任体系结构中的动态安全边界。本文设计了一种适用于零信任体系结构的差分隐私方案。它在集中式和局部DP场景下具有一致的隐私表示和相同的噪声机制,能够平衡隐私保护的强度和隐私机制的灵活性。我们在实验中验证了该算法,使用最大期望估计方法可以在相同的安全级别下获得与传统方法相同甚至更好的效用结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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