Titlebook: Database Systems for Advanced Applications; 24th International C Guoliang Li,Jun Yang,Yongxin Tong Conference proceedings 2019 Springer Nat

燈絲

Multiple Privacy Regimes Mechanism for Local Differential Privacytinuous distribution. We also provide an Adapt estimator which assigns users to use different LDP schemes based on their regimes, and it performs better than the estimator with only one fixed LDP scheme. Experiments show that our methods provide a higher level of accuracy than previous proposals in

小蟲

Privacy Preserving Elastic Stream Processing with Clouds Using Homomorphic Encryptiondes significant results which is 10% to 17% improvement of average latency in the case of email filter benchmark and EDGAR benchmarks respectively. Furthermore, EDGAR add/subtract operations and comparison operations showed 6.13% and 26.17% average latency improvements respectively. These promising

寬大

Select the Best for Me: Privacy-Preserving Polynomial Evaluation Algorithm over Road Network reduce the computation overhead, we introduce an influence model to store the encrypted point data (restaurant). Besides the stronger security, this work is a practical polynomial evaluation algorithm over the road network. The practicality is mainly manifested in two aspects: evaluation over multi

羞辱

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Database Systems for Advanced Applications978-3-030-18579-4Series ISSN 0302-9743 Series E-ISSN 1611-3349

Consensus

https://doi.org/10.1007/978-3-031-26779-6 model makes simplifying assumptions in order to produce said estimates in a timely manner. These assumptions lead to selectivity estimation errors that have dramatic effects on the quality of the resulting query execution plans. A convenient assumption that is ubiquitous among current cost models i

Audiometry

大火

https://doi.org/10.1057/978-1-349-95359-2nt of these data is limited and the access to EHRs is difficult due to the issue of patient privacy. Thus high quality synthetic EHRs data is necessary to alleviate these issues. In this paper, we propose a Sequentially Coupled Generative Adversarial Network (SC-GAN) to generate continuous patient-c

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https://doi.org/10.1057/978-1-349-95359-2 in the intensive care unit (ICU). However, the central role of diagnosis in clinical practice is challenged by evidence that does not always benefit patients and that factors other than disease are important in determining patient outcome. To streamline the diagnostic process in daily routine and a

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