Privacy Preserving Data Mining With Multi Keyword Ranked Search for Medical Data
1MP.Subhashree*, Research Scholar, Sathyabama Institute Of Science & Technology
2G.Gunasekaran, Principal J.N.N Institute of Engineering Chennai
Manuscript received on December 13, 2019. | Revised Manuscript received on December 23, 2019. | Manuscript published on January 10, 2020. | PP: 21-25 | Volume-9 Issue-3, January 2020. | Retrieval Number: B7375129219/2020©BEIESP | DOI: 10.35940/ijitee.B7375.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Privacy Preserving Data Mining (PPDM) maintains the privacy of data stored in cloud. This work aims to protect outsourced data in cloud, and also permit multi keyword search over the encrypted data in a secure way by NLP process without downloading and decrypting all files. Different methods for privacy preservation were analyzed and randomization for multilevel trust is proposed along with an efficient method for keyword search in cloud.
Keywords: Cloud, Privacy Preservation, Multi keyword Search, NLP.
Scope of the Article: Data Mining