A survey on privacy issues and privacy preservation in spatial data mining

The process of discovering interesting and previously unknown, but potentially useful patterns from large spatial datasets is called spatial data mining. Extracting interesting and useful patterns from spatial datasets is more difficult than extracting the corresponding patterns from traditional numeric and categorical data due to the complication of spatial data types, spatial associations and correlation between them. Spatial Information may not only include spatial or geographical information or symbols but can also contain personal information like a person´s name, mobile phone numbers linked with their address. Spatial data mining operation on such databases may not only extract required interesting patterns but may also reveal the sensitive and personal information which are associated with spatial database. An intruder can pose challenges to individual privacy by extracting the spatial data mining results or patterns and linking the data in various situations, previous knowledge and other information obtained from heterogeneous sources. This paper focus on various possibilities through which privacy of an individual can be easily violated in spatial data mining operation. Different techniques are proposed which can preserve the privacy of an individual in spatial data mining operation.