The compilation of digital data by various private and government organizations has created incredible occasion for knowledge based decision making. Data mining extracts interesting patterns from a huge database. Driven by reciprocated benefits, there is a high demand for data exchange among the interested parties. Original data includes sensitive information with reference to individuals, and distributing such data results in individual privacy violation. Achieving privacy and data integrity is considered to be demanding tasks in data mining. Privacy preservation is the most vital aspect for an individual as he should not be humiliated by an antagonist. This paper provides a study on the use of various perturbation methods that ensure privacy while applying any data mining algorithm.

translation, scaling, shearing, clustering, normalization.