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On syntactic anonymity and differential privacy
2013 IEEE 29th International Conference on Data Engineering Workshops (ICDEW), 2013Recently, there has been a growing debate over approaches for handling and analyzing private data. Research has identified issues with syntactic anonymity models. Differential privacy has been promoted as the answer to privacy-preserving data mining. We discuss here issues involved and criticisms of both approaches, and conclude that both have their ...
Chris Clifton, Tamir Tassa
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Asymmetric Differential Privacy
2022 IEEE International Conference on Big Data (Big Data), 2022Shun Takagi +3 more
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Linking Differential Identifiability with Differential Privacy
2018The problem of preserving privacy while mining data has been studied extensively in recent years because of its importance for enabling sharing data sets. Differential Identifiability, parameterized by the probability of individual identification \(\rho \), was proposed to provide a solution to this problem.
Anis Bkakria +2 more
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A Critical Review on the Use (and Misuse) of Differential Privacy in Machine Learning
ACM Computing Surveys, 2023Josep Domingo-Ferrer +2 more
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Applications of Differential Privacy in Social Network Analysis: A Survey
IEEE Transactions on Knowledge and Data Engineering, 2021Xiuzhen Cheng, Honglu Jiang, Jiguo Yu
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A Survey on Differential Privacy for Unstructured Data Content
ACM Computing Surveys, 2022Jinjun Chen
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Differential Privacy Techniques for Cyber Physical Systems: A Survey
IEEE Communications Surveys and Tutorials, 2020Muneeb Ul Hassan +2 more
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More Than Privacy: Applying Differential Privacy in Key Areas of Artificial Intelligence
IEEE Transactions on Knowledge and Data Engineering, 2022Wanlei Zhou, Philip Yu, Dayong Ye
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