It is often difficult to share denominated data between different organisations and researchers due to ethical constraints related to respondent's confidentiality. This is a frequent reality in healthcare, given the inherent sensitivity of the data involved. One option in this case is to not share the data directly, but rather to provide access to it via a tool that controls the risk of disclosure of the queries made and allows only those it considers safe. DataSHIELD is such a tool that has been proposed to protect the confidentiality of a dataset, and which is used via the statistical software R. It also allows statistical analyses to be carried out on several datasets hosted in different locations, always ensuring the confidentiality of the respondents. In this project, we are interested in the confidentiality guarantees provided by the software, and in its limitations. In particular, we study the potential uses of the software for advanced statistical analyses, such meta-analyses and the use of neural networks.