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Titlebook: Data Privacy Management, Cryptocurrencies and Blockchain Technology; ESORICS 2021 Interna Joaquin Garcia-Alfaro,Jose Luis Muñoz-Tapia,Migue

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发表于 2025-3-21 17:21:34 | 显示全部楼层 |阅读模式
书目名称Data Privacy Management, Cryptocurrencies and Blockchain Technology
副标题ESORICS 2021 Interna
编辑Joaquin Garcia-Alfaro,Jose Luis Muñoz-Tapia,Miguel
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Data Privacy Management, Cryptocurrencies and Blockchain Technology; ESORICS 2021 Interna Joaquin Garcia-Alfaro,Jose Luis Muñoz-Tapia,Migue
描述This book constitutes the refereed proceedings and revised selected papers from the 16th International Workshop on Data Privacy Management, DPM 2021, and the 5th International Workshop on Cryptocurrencies and Blockchain Technology, CBT 2021, which were held online on October 8, 2021, in conjunction with ESORICS 2021. The workshops were initially planned to take place in Darmstadt, Germany, and changed to an online event due to the COVID-19 pandemic..The DPM 2021 workshop received 25 submissions and accepted 7 full and 3 short papers for publication. These papers were organized in topical sections as follows: Risks and privacy preservation; policies and regulation; privacy and learning..For CBT 2021 6 full papers and 6 short papers were accepted out of 31 submissions. They were organized in topical sections as follows: Mining, consensus and market manipulation; smart contracts and anonymity..
出版日期Conference proceedings 2022
关键词anonymity and untracability; artificial intelligence; computer security; consensus mechanisms; cryptogra
版次1
doihttps://doi.org/10.1007/978-3-030-93944-1
isbn_softcover978-3-030-93943-4
isbn_ebook978-3-030-93944-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2022
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Community Research for Community Developmentccuracy. The main idea of SPGC is to .. We also created an implementation of SPGC and used it in experiments to measure its accuracy and training time. The results show that SPGC is more accurate than a naive protocol based on local differential privacy by up to 5.6%.
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Interdependent Privacy Issues Are Pervasive Among Third-Party Applicationsat interdependent privacy risks are enabled by certain permissions in all platforms studied, and actual apps request these permissions instantiating these risks. We also identify potential risk signals, and discuss solutions which could improve transparency and control for users, developers and platform owners.
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SPGC: An Integrated Framework of Secure Computation and Differential Privacy for Collaborative Learnccuracy. The main idea of SPGC is to .. We also created an implementation of SPGC and used it in experiments to measure its accuracy and training time. The results show that SPGC is more accurate than a naive protocol based on local differential privacy by up to 5.6%.
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Community Research for Community Developmentgregator sends the merged decision tree to the distributed devices. Therefore, we aim to build a joint machine learning model based on the data from multiple devices while offering .-anonymity to the participants.
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