Oct 22, 2024 · We propose a new definition for privacy, called δ \delta -privacy, for privacy preserving data mining. The intuition of this work is, ...
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Jan 31, 2024 · Differential privacy can also be used for streaming data allowing the privacy-preserving release of information in an online manner with a ...
Dec 1, 2024 · Differential Privacy is a powerful framework for ensuring privacy in data analysis by adding controlled noise to computations.
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Differential privacy provides a formal framework to quantify and limit privacy risks, ensuring that the outputs of data queries do not compromise individual ...
Jan 11, 2014 · In this research we present a novel approach to the concept change detection problem. Change detection is a fundamental issue with data ...
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Apr 13, 2023 · A differential privacy protection algorithm for network sensitive information based on singular value decomposition is proposed.
We design, to the best of our knowledge, the first differentially private (DP) stream processing system at scale. Our system --Differential Privacy SQL ...
A distributed and privacy-preserving algorithm for discovering the heavy hitters in a population of user-generated data streams that eliminates the need to ...
Furthermore, due to satisfying the triangle inequality, WDP can handle basic sequential composition, group privacy, and advanced composition problems better.
Nov 20, 2023 · Online active learning is a paradigm in machine learning that aims to select the most informative data points to label from a data stream.