Research on a New Privacy-Preserving Algorithm of Association Rules Based on Parameter Perturbation
نویسندگان
چکیده
Due to the reason that the randomness of the parameters in the MASK algorithm always leads to the volatility and uncertainty of the mining results, this paper proposed an optimization algorithm for the maximum likelihood estimation of the parameters to choose a parameter that is most approximate to the common parameters from the parameter group that has been generated randomly. Such a parameter generated as above represented all of the parameters in the parameter group. The simulation experiment proves that the application of such a parameter has reduced the great volatility hidden in the mining results to some extent.
منابع مشابه
Introducing an algorithm for use to hide sensitive association rules through perturb technique
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