Randomized Response, Statistical Disclosure Control and Misclassificatio: a Review

By A. Hout, P. G. Heijden. 2002

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Classification in the Presence of Label Noise: A Survey (2014, background): “Hout and Heijden [28] discuss the case of artiﬁcial label noise which can be intentionally introduced after data collection to preserve privacy.”
Composition attacks and auxiliary information in data privacy (2008, methodology): “, [35]), or by injecting randomness into the algorithm used to analyze the data (e.”
Item Randomized-Response Models for Measuring Noncompliance: Risk-Return Perceptions, Social Influences, and Self-Protective Responses (2007, unknown): “extends previously proposed latent class and logistic regression models for RR data (Dayton & Scheers, 1997; Maddala, 1983; Scheers & Dayton, 1988; van den Hout & van der Heijden, 2002, 2004 ).”
A note on the comparison of some randomized response procedures (2007, methodology): “Recommendations and successful applications of the Kuk’s procedure have been also reported in van den Hout and van der Heijden (2002) .”