We describe output perturbation techniques that allow for a provable, rigorous sense of individual privacy. Examples where the techniques are effective span frombasic statistical computations to sophisticated machine learning algorithms.
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Nissim, K. (2008). Private Data Analysis via Output Perturbation. In: Aggarwal, C.C., Yu, P.S. (eds) Privacy-Preserving Data Mining. Advances in Database Systems, vol 34. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-70992-5_16
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DOI: https://doi.org/10.1007/978-0-387-70992-5_16
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