Titlebook: Security and Privacy in Web 3.0; Meng Shen,Xiangyun Tang,Liehuang Zhu Book 2024 The Editor(s) (if applicable) and The Author(s), under exc

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Meng Shen,Xiangyun Tang,Liehuang ZhuDelivers a comprehensive introduction of security and privacy in Web 3.0, along with practical defense frameworks.Explores privacy computing, data asset protection, and behavior analysis within the ar

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Digital Privacy and Securityhttp://image.papertrans.cn/s/image/863529.jpg

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https://doi.org/10.1007/978-981-97-5752-7Web 3; 0; Blockchain; Privacy Protection; Privacy Computing; Federated Learning, ; Device Authentication;

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978-981-97-5754-1The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor

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Security and Privacy in Web 3.0978-981-97-5752-7Series ISSN 2731-992X Series E-ISSN 2731-9938

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Security and Privacy Defense Framework for Web 3.0,.0, while offering numerous advantages, presents unique challenges such as ensuring privacy protection, authentication and behavior identification, and the auditing of data asset transactions. To navigate these complexities, we propose a comprehensive security and privacy defense framework for Web 3

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Verifiable Privacy-Preserving Federated Learning in Web 3.0,plete sovereignty and ownership over their data in Web 3.0. However, the high degree of personal control over data limits the mobility and interoperability of data, forming data silos that restrict the development of Web 3.0. As an advanced paradigm that breaks down data silos, federated learning ca