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a r t i c l e i n f o Identity disclosure is one of the most serious privacy concerns in today's information age. A well-known method for protecting identity disclosure is k-anonymity. A dataset provides k-anonymity protection if the information for each individual in the dataset cannot be distinguished from at least k − 1 individuals whose information also(More)
An association mapping of quantitative trait loci (QTLs) regulating the concentrations of eight elements in brown rice (Oryza sativa L.) was performed using USDA mini-core subset cultivated in two different environments. In addition, correlation between the grain elemental concentrations was also studied. A total of 60 marker loci associated with 8 grain(More)
Due to growing concerns about the privacy of personal information, organizations that use their customers' records in data mining activities are forced to take actions to protect the privacy of the individuals. A frequently used disclosure protection method is data perturbation. When used for data mining, it is desirable that perturbation preserves(More)
Regression techniques can be used not only for legitimate data analysis, but also to infer private information about individuals. In this paper, we demonstrate that regression trees, a popular data-analysis and data-mining technique, can be used to effectively reveal individuals' sensitive data. This problem, which we call a "regression attack," has not(More)
—Multiple-model approach provides the state-of-the-art solutions to many problems involving estimation, filtering, control, and/or modeling. One of the most important problems in the application of the multiple-model approach is the design of the model set used in a multiple-model algorithm. To our knowledge, however, it has never been addressed(More)