How to automatically identify and classify sensitive attributes(fields) of structured datasets, which are confused by code in the production environment, has become a bottleneck for structured data privacy protection. This paper proposed an automatic recognition and classification algorithm of sensitive attributes. This algorithm introduced information entropy to define the sensitivity of the attribute, identified and quantified sensitivity of the sensitive attributes by sensitivity clustering of attri-butes and association rules mining among attributes. Further, by analyzing the mutual information correlations and association rules among grouped the sensitive attribute clusters, the sensitive attributes and quantified the average sensitive metrics of these groups. Thus, this algorithm achieved the classifying of the sensitive attributes. Experiments show that the algorithm can identify the sensitive attributes of any structured dataset and classify the sensitive attributes, with higher efficiency and accuracy. Comparison shows that this algorithm can achieve both recognition and classification of sensitive attributes. It's not necessary to know the characteristics of attributes and sensitive feature dictionary. Both of the correlation and association among attributes are took into account by this algorithm.

[2020-10-05] Printed Article /doc/2019.05.0187/v2