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DC Field | Value | Language |
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dc.contributor.author | Vashi, Devendra I. | - |
dc.date.accessioned | 2015-07-10T07:44:29Z | - |
dc.date.available | 2015-07-10T07:44:29Z | - |
dc.date.issued | 2014-06 | - |
dc.identifier.citation | National Conference on Analysis, Design & Research in Engineering, Technology & Sciences – 2014, KIRC-382721,Gujarat, And AES Journals in Engineering , Technology, Science and Management | en_US |
dc.identifier.uri | http://hdl.handle.net/123456789/5514 | - |
dc.description | International Journal Of Emerging Technologies And Applications In Engineering, Technology And Sciences (IJ-ETA-ETS) | en_US |
dc.description.abstract | While sharing the private data, privacy preserving is becoming an increasingly significant issue. Various privacy preserving data mining techniques like data modification and secure multiparty computation based on the different aspects. analyze the comparative study of all techniques so Issues about privacy-preserving data mining have emerged globally. The aim of privacy-preserving data mining is to find the right balance between maximizing analysis results that are useful for the common good and keeping the inferences that disclose private information about organizations or individuals at a minimum. | en_US |
dc.publisher | IJ-ETA-ETS | en_US |
dc.relation.ispartofseries | ITFCA008-7; | - |
dc.subject | Data Mining | en_US |
dc.subject | Privacy Preserving Data Mining | en_US |
dc.subject | Randomization | en_US |
dc.subject | Anonymization | en_US |
dc.subject | Sequential Pattern Hiding | en_US |
dc.subject | Data Perturbation | en_US |
dc.subject | Computer Faculty Paper | en_US |
dc.subject | Faculty Paper | en_US |
dc.subject | ITFCA008 | en_US |
dc.title | Survey On Privacy Preserving Data Mining Techniques | en_US |
dc.type | Faculty Papers | en_US |
Appears in Collections: | Faculty Papers, CE |
Files in This Item:
File | Description | Size | Format | |
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ITFCA008-7.pdf | ITFCA008-7 | 204.11 kB | Adobe PDF | ![]() View/Open |
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