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Answer Posted / Gyaneshchandra Sharma
Differential Privacy is a technique used to protect individual data privacy in statistical analysis. It adds noise to the data in such a way that the presence or absence of an individual in the dataset has a negligible impact on the output of the analysis. This means that even if an adversary has access to the analyzed data, they cannot easily infer information about any particular individual. Differential Privacy can be achieved through several methods like Laplace Mechanism and Gaussian Mechanism.
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