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Traditional access control models aim to prevent data leakage via direct accesses. A direct access occurs when a requester performs his query directly into the desired object, however these models fail to protect sensitive data from being accessed with inference channels. An inference channel is produced by the combination of a legitimate response which the user receives from the system and metadata. Detecting and removing inference in database systems guarantee a high quality design in terms of data secrecy and privacy. Parting from the fact that data distribution exacerbates inference problem, we give in this paper a survey of the current and emerging research on the inference problem in both centralized and distributed database systems and highlighting research directions in this field.