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This paper presents a privacy preserving clustering technique using hybrid approach. The technique mainly exploits a combination of isometric transformations i.e. translation, rotation and reflection transformations along with a secure random function in order to provide secrecy of user-specified attributes without losing accuracy in results. The proposed method was tested and evaluated in terms of...
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