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Review on k -Nearest Neighbor Classification over Semantically Secure Encrypted Relational Data

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Swathy J., Surya S.R.

Swathy J. and Surya S.R.. Article: Review on k -Nearest Neighbor Classification over Semantically Secure Encrypted Relational Data. International Journal of Computer Applications 133(8):1-4, January 2016. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

	author = {Swathy J. and Surya S.R.},
	title = {Article: Review on k -Nearest Neighbor Classification over Semantically Secure Encrypted Relational Data},
	journal = {International Journal of Computer Applications},
	year = {2016},
	volume = {133},
	number = {8},
	pages = {1-4},
	month = {January},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}


Data mining has wide variety of real time application in many fields such as financial, telecommunication, biological, and among government agencies. Classification is the one of the main task in data mining. For the past few years, due to the increment in various privacy problem, many conceptual and feasible solution to the classification problem have been proposed under different certainty prototype. With the increment of cloud computing users have an opportunity to offload the data and processing to the cloud, in an encrypted form. The data in the cloud are in encrypted form, existing privacy preserving classification systems are not relevant. This paper reviews how to perform privacy preserving k-NN classification over encrypted data in the cloud. The recommended protocol preserves privacy of data, protect the user query, and hide the access mode.


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Security, k-NN classifier, outsourced databases, encryption