Reconstruction attacks aim to infer sensitive information about individuals in a dataset by using statistical outputs provided by the dataset's curator. For example, if a dataset includes anonymous health information, an attacker might use statistical analysis to deduce the health status of specific individuals. These attacks use methods like solving sets of linear queries about the dataset, where the accuracy of these queries can lead to almost complete reconstruction of the private data.