A Brief Survey of Secrecy Protective Data Mining (SPDM)

V. Uthaman

Abstract


The secrecy protective data mining is assuming urgent part go about as rising innovation to perform different data mining operations on private data and to pass on data in a secured approach to ensure delicate data. Many sorts of system, for example, randomization, secured aggregate calculations and k-anonymity have been recommended with a specific end goal to execute secrecy protective data mining. In this overview paper, on ebb and flow examines made on secrecy protective data mining strategy with fuzzy logic, neural network learning, secured total and different encryption calculation is displayed. This will empower to get a handle on the different difficulties confronted in secrecy protective data mining and furthermore help us to discover best reasonable procedure for different data condition.

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References


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