چکیده مقاله
There exists an enormous amount of useful information gathered by statistical agencies However, the privacy issues of involved entities limit them for public usages Different computational privacy models are suggested to protect the privacy of individuals during data publishing such as anonymity In a anonymous dataset, each combination of identifying attributes occurs in at least records Microaggregation is a successful mechanism to realize anonymity However, it is proved to be NP hard in general This paper addressed the problem of multivariate microaggregation and introduces a compact encoding to solve it using an evolutionary approach Experimental results confirm the superiority of the proposed method in 88% of test cases in compare with similar studies in the literature
کلیدواژهها
نویسندگان
Reza Mortazavi
School of Engineering, Damghan University, Damghan, Iran;
Seyedeh Hamideh Erfani
School of Engineering, Damghan University, Damghan, Iran;
شیوه ارجاع
Mortazavi, Reza and Hamideh Erfani, Seyedeh,1398,Multivariate microaggregation based on an evolutionary approach,3rd International Conference on Soft Computing,Rudsar
ارائهشده در
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