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Titlebook: Data Privacy Management, Cryptocurrencies and Blockchain Technology; ESORICS 2020 Interna Joaquin Garcia-Alfaro,Guillermo Navarro-Arribas,J

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樓主: 嚴厲
11#
發(fā)表于 2025-3-23 10:37:51 | 只看該作者
PDP-ReqLite: A Lightweight Approach for the Elicitation of Privacy and Data Protection Requirementsamed PDP-ReqLite initially inspired from ProPAn that introduces new artifacts for the documentation of personal data and information flows in a system-to-be. The purpose of PDP-ReqLite is to improve usability and applicability by reducing documentation overhead and complexity, and by introducing mea
12#
發(fā)表于 2025-3-23 17:01:29 | 只看該作者
13#
發(fā)表于 2025-3-23 18:04:08 | 只看該作者
Tracking the Invisible: Privacy-Preserving Contact Tracing to Control the Spread of a Virusd on private set intersection between physical contact histories of individuals (that are recorded using smart phones) and a centralized database (run by a health authority) that keeps the identities of the positively diagnosed patients for the disease. Proposed solution protects the location privac
14#
發(fā)表于 2025-3-23 22:59:41 | 只看該作者
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發(fā)表于 2025-3-24 06:05:32 | 只看該作者
16#
發(fā)表于 2025-3-24 09:23:54 | 只看該作者
Community policing in the United Statesking methods proposed to reduce the number of comparisons, they fall short in providing an efficient and effective solution for linking multiple large databases. Further, all private blocking methods are largely dependent on data. In this paper, we propose a novel private blocking method addressing
17#
發(fā)表于 2025-3-24 14:18:51 | 只看該作者
https://doi.org/10.1007/978-3-319-53396-4 protection remains a challenge. In addition to this, existing approaches do not work well with high-dimensional data, since it is difficult to develop good groupings without incurring excessive information loss. Our work aims to overcome these challenges by proposing a hybrid approach, combining se
18#
發(fā)表于 2025-3-24 18:20:07 | 只看該作者
Community Policing - A European Perspectiveable in an anonymization algorithm, that are combinations of minimization of data alteration, maximization of .-diversity and minimization of .-closeness. At the end, this study provides comparative experimental results of these strategies on the ., a commonly used data set within the anonymization
19#
發(fā)表于 2025-3-24 19:52:49 | 只看該作者
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發(fā)表于 2025-3-25 01:20:58 | 只看該作者
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