An Efficient KNN Classification by using Combination of Additive and Multiplicative Data Perturbation for Privacy Preserving Data Mining

Bhupendra Kumar Pandya; Umesh kumar Singh; Keerti Dixit

doi:https://doi.org/10.14445/22315381/IJETT-V22P261

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Volume 22 | Number 2 | Year 2015 | Article Id. IJETT-V22P261 | DOI : https://doi.org/10.14445/22315381/IJETT-V22P261

An Efficient KNN Classification by using Combination of Additive and Multiplicative Data Perturbation for Privacy Preserving Data Mining

Bhupendra Kumar Pandya, Umesh kumar Singh, Keerti Dixit

Citation :

Bhupendra Kumar Pandya, Umesh kumar Singh, Keerti Dixit, "An Efficient KNN Classification by using Combination of Additive and Multiplicative Data Perturbation for Privacy Preserving Data Mining," International Journal of Engineering Trends and Technology (IJETT), vol. 22, no. 2, pp. 290-295, 2015. Crossref, https://doi.org/10.14445/22315381/IJETT-V22P261

Abstract

Nowadays there is huge amount of data being collected and stored in databases everywhere across the globe. Recently, there has been a growing interest in the data mining area, where the objective is the discovery of knowledge that is correct and of high benefit for users. Data miming consists of a set of techniques that can be used to extract relevant and interesting knowledge from data. Data mining has several tasks such as association rule mining, classification and prediction, and clustering. Classification techniques are supervised learning techniques that classify data item into predefined class label. It is one of the most useful techniques in data mining to build classification models from an input data set. The used classification techniques commonly build models that are used to predict future data trends. In this research paper we analysis CAMDP (Combination of Additive and Multiplicative Data Perturbation) technique for KNN classification as a tool for privacy-preserving data mining. We can show that KNN Classification algorithm can be efficiently applied to the transformed data and produce exactly the same results as if applied to the original data.

Keywords

CAMDP, KNN classification.

References

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