Implementation of Attribute Based Symmetric Encryption through Vertically Partitioned Data in PPDM
Devendrasinh Vashi1, H B Bhadka2, Kuntal Patel3, Sanjay Garg4

1Devendrasinh Vashi*, Computer Science Department, Nirma University, Ahmedabad, India.
2Dr. H B Bhadka, Faculty of Computer Science, C U Shah University, Wadhwan, India.
3Dr. Kuntal Patel, School of Computer Studies, Ahmedabad University, Ahmedabad, India.
4Dr. Sanjay Garg, Computer Science Department, Nirma University, Ahmedabad, India.
Manuscript received on September 12, 2019. | Revised Manuscript received on October 15, 2019. | Manuscript published on October 30, 2019. | PP: 868-874 | Volume-9 Issue-1, October 2019 | Retrieval Number: A9395109119/2019©BEIESP | DOI: 10.35940/ijeat.A9395.109119
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Abstract: The aim of this research article is to implement the symmetric encryption techniques on the vertically partitioned database table. In privacy-preserving data mining mainly sensitive attributes to be protected so that privacy will maintain during data mining. In this proposed algorithm the datasets partitioned in the three different sets. Then for each table for the selected attributes only one symmetrical encryption as well as different symmetric encryption is implemented. Initial data size, encryption execution time and data size after encryption are observed for each file of different data size. In result and analysis examined the performance of execution time and memory occupied after each encryption techniques is discussed and found that hybrid algorithm of using different symmetric encryption for each partitioned table is good as compared to implementing only one encryption on each partitioned table. This algorithm is mainly useful to provide privacy in PPDM in case of distributed data base of health care organizations.
Keywords: Privacy preserving, Vertically partitioned data, Data Mining, encryption.