| 引用本文： |
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张江江,公备,张玉,沈昌祥,左晓栋.物联网数据全生命周期可信隐私保护研究综述[J].信息安全学报,已采用 [点击复制]
- Zhang Jiangjiang,Gong Bei,Zhang Yu,Shen Changxiang,Zuo Xiaodong.Survey on trusted privacy preserving in the entire lifecycle of IoT data[J].Journal of Cyber Security,Accept [点击复制]
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| 摘要: |
| 物联网数据正逐步成为推动数字经济发展的核心资源，其所承载的价值正在不断释放。然而，在加快建设数据要素市场的过程中，仍面临诸多现实挑战，例如数据可信供给质量不高、流通机制不完善、数据应用潜力挖掘不足以及隐私保护能力薄弱等。随着物联网设备生成的海量、多源、敏感性强的数据不断增长，如何在保障数据隐私的前提下实现数据的高效、安全、可信流通，已成为当前亟待解决的关键问题。特别是在数据价值释放与隐私保护之间寻找有效平衡，对于数字化转型的可持续发展具有重要意义。本文首先阐述了在推动物联网数据安全可信流通过程中，兼顾数据要素价值实现与隐私保护的必要性，强调可信性与隐私保护应融合于数据治理机制之中。其次，系统介绍了物联网的基本组成架构、数据全生命周期管理模型，并详细分析了当前主流的隐私保护技术理论，包括差分隐私、安全多方计算与联邦学习等，说明其在分布式环境下的重要应用价值。然后，从数据源头可信、传输过程安全、共享机制可靠以及应用阶段可控四个关键环节出发，系统梳理了当前研究现状、存在的主要安全风险、应对策略及技术发展瓶颈。最后，以物联网数据安全可信流通为研究导向，展望了物联网数据全生命周期隐私保护的未来研究趋势，旨在为建设高效、安全、透明、以隐私为中心的数据要素市场提供理论指导与技术支撑。 |
| 关键词: 物联网数据 全生命周期 隐私保护 数据安全可信流通 数据要素 |
| DOI： |
| 投稿时间：2025-03-28修订日期：2025-06-20 |
| 基金项目:国家自然科学基金项目（面上项目，重点项目，重大项目） |
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| Survey on trusted privacy preserving in the entire lifecycle of IoT data |
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Zhang Jiangjiang1, Gong Bei2, Zhang Yu3, Shen Changxiang2, Zuo Xiaodong4
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| (1.Shanxi University;2.Beijing University of Technology;3.Zhengzhou Normal University;4.University of science and technology of China) |
| Abstract: |
| The Internet of Things (IoT) has become an essential enabler of the digital economy, with IoT-generated data serving as a fundamental production factor. However, the effective construction of a robust data element market still faces numerous challenges. These include the low quality and reliability of trusted data sources, inadequate mechanisms for efficient and secure data circulation, limited exploitation of the full potential of IoT data applications, and in-sufficient capabilities for privacy and security protection. As IoT devices generate vast amounts of heterogeneous and often sensitive data, ensuring the secure and trustworthy flow of such data is critical. In particular, the ability to balance the value extraction from IoT data with rigorous privacy preservation is a core issue that must be addressed to support sustainable digital transformation. This paper first underscores the importance of safeguarding personal and sensitive data while maximizing the utility and value of data elements in the process of trusted IoT data circula-tion. It emphasizes that data trustworthiness and privacy protection are not mutually exclusive, but must instead be integrated into the design of data governance frameworks. Following this, the basic architectural components of IoT systems are introduced, along with a detailed explanation of the IoT data lifecycle management model. The discus-sion also incorporates relevant theoretical foundations in privacy-preserving technologies, such as differential pri-vacy, secure multi-party computation, and federated learning, which have become critical tools in securing data in decentralized environments. Next, the paper provides an in-depth analysis of the current research landscape across four key dimensions: trusted data sources, secure data transmission, trustworthy data sharing, and reliable data ap-plication. Each stage of the data lifecycle is examined in terms of existing security threats, technical approaches, and remaining research gaps. Finally, with secure and trustworthy circulation of IoT data as the central research goal, the paper discusses future research trends and directions in privacy protection across the entire data lifecycle. These insights aim to guide the development of intelligent and secure data flow mechanisms, ultimately contributing to the establishment of a transparent, efficient, and privacy-conscious data element market. |
| Key words: IoT data entire life cycle privacy preserving safe and reliable data circulation data elements |
