Research on Differential Privaty for Decision Tree Release Technology

doi:10.3969/j.issn.1006-2475.2017.03.013

Abstract

Abstract:

Privacy disclosure issue is becoming more and more serious due to big data. We proposed a differential private generalization data publishing algorithm for decision

tree. The algorithm is based on the noninteractive model， in the process of attribute segmentation by combining similar branch to reduce the overall noise， and keeps more of

original information， so it can improve the accuracy of classification. According to the need of exponential mechanism， adaptive allocation privacy budget， compared with the

previous algorithms， under the condition of the same privacy budget it can make the data more differentiated， and decision tree classification accuracy is higher. The

experimental results also prove the validity and superiority of this algorithm.

Key words: , generalization； differential privacy； decision tree； data release； privacy preserving

CLC Number:

TP393

CHEN Yang， YU Shoujian. Research on Differential Privaty for Decision Tree Release Technology[J]. Computer and Modernization, 2017, 0(3): 59-.

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