In differential privacy, randomised mechanisms are essential for ensuring the privacy of individuals in a dataset. These mechanisms introduce a controlled level of uncertainty in the data analysis process, making it difficult to ascertain whether a specific individual's data was used in the computation. The mechanism operates by providing probabilistic responses to queries, where the response is slightly altered by random noise. This ensures that the results of the analysis are similar, regardless of the presence or absence of any single individual's data, thus protecting their privacy. The randomness imbued by these mechanisms is key to fulfilling the strict criteria of differential privacy.