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A Preliminary Investigation of the Impact of Gaussian Versus t-Copula for Data Perturbation.

, , и . Privacy in Statistical Databases, том 5262 из Lecture Notes in Computer Science, стр. 127-138. Springer, (2008)

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Muralidhar Deshpande

 

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Perturbing Nonnormal Confidential Attributes: The Copula Approach., , и . Manag. Sci., 48 (12): 1613-1627 (2002)Statistical Information Recovery from Multivariate Noise-Multiplied Data, a Computational Approach., , , и . Trans. Data Priv., 11 (1): 23-45 (2018)Can You Have Your Cake and Eat It Too? Sharing Healthcare Data Without Compromising Privacy and Confidentiality., и . AMCIS, стр. 294. Association for Information Systems, (2005)A Preliminary Investigation of the Impact of Gaussian Versus t-Copula for Data Perturbation., , и . Privacy in Statistical Databases, том 5262 из Lecture Notes in Computer Science, стр. 127-138. Springer, (2008)An Improved Security Requirement for Data Perturbation with Implications for E-Commerce., , и . Decis. Sci., 32 (4): 683-698 (2001)An Investigation of Model-Based Microdata Masking for Magnitude Tabular Data Release., , и . Privacy in Statistical Databases, том 7556 из Lecture Notes in Computer Science, стр. 47-62. Springer, (2012)Why Swap When You Can Shuffle? A Comparison of the Proximity Swap and Data Shuffle for Numeric Data., , и . Privacy in Statistical Databases, том 4302 из Lecture Notes in Computer Science, стр. 164-176. Springer, (2006)A theoretical basis for perturbation methods., и . Stat. Comput., 13 (4): 329-335 (2003)General Confidentiality and Utility Metrics for Privacy-Preserving Data Publishing Based on the Permutation Model., , и . CoRR, (2020)Reverse Mapping to Preserve the Marginal Distributions of Attributes in Masked Microdata., , и . Privacy in Statistical Databases, том 8744 из Lecture Notes in Computer Science, стр. 105-116. Springer, (2014)