Titlebook: Data and Applications Security and Privacy XXXVII; 37th Annual IFIP WG Vijayalakshmi Atluri,Anna Lisa Ferrara Conference proceedings 2023

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书目名称Data and Applications Security and Privacy XXXVII影响因子(影响力)




书目名称Data and Applications Security and Privacy XXXVII影响因子(影响力)学科排名




书目名称Data and Applications Security and Privacy XXXVII网络公开度




书目名称Data and Applications Security and Privacy XXXVII网络公开度学科排名




书目名称Data and Applications Security and Privacy XXXVII被引频次




书目名称Data and Applications Security and Privacy XXXVII被引频次学科排名




书目名称Data and Applications Security and Privacy XXXVII年度引用




书目名称Data and Applications Security and Privacy XXXVII年度引用学科排名




书目名称Data and Applications Security and Privacy XXXVII读者反馈




书目名称Data and Applications Security and Privacy XXXVII读者反馈学科排名

南极

https://doi.org/10.1007/978-3-642-85098-1ork that supports organizations in implementing and performing ACP maintenance. Third, we present a maintenance case study in which we implemented maintenance capabilities for a real-world ACP dataset that allowed us to significantly improve its quality.

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Differentially Private Streaming Data Release Under Temporal Correlations via Post-processingl and transform it into nonlinear constrained programming. Our experiments on synthetic datasets show that the proposed approach significantly improves the utility and accuracy of differentially private data by nearly a hundred times in terms of mean square error when a strict privacy budget is given.

诙谐

Maintain High-Quality Access Control Policies: An Academic and Practice-Driven Approachork that supports organizations in implementing and performing ACP maintenance. Third, we present a maintenance case study in which we implemented maintenance capabilities for a real-world ACP dataset that allowed us to significantly improve its quality.

表主动

0302-9743 nce, July 19–21, 2023.  .The 19 full papers presented together with 5 short papers were carefully reviewed and selected from 56 submissions. The conference focuses on secure data sharing; access control and vulnerability assessment; machine learning; and mobile applications..978-3-031-37585-9978-3-0

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(Local) Differential Privacy has NO Disparate Impact on Fairness With LDP, users can perturb their data on their devices before sending it out for analysis. However, as the collection of multiple sensitive information becomes more prevalent across various industries, collecting a single sensitive attribute under LDP may not be sufficient. Correlated attributes i

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