While l-diversity provides a guarantee of the stronger privacy than k-anonymity, the adequate l-diversity may not be achieved with natural occurrence of the sensitive values.
The l-diversity model handles a few of the weaknesses in the k-anonymity model in which protected identities to the level of k-individuals is not equal to protecting the corresponding sensitive values that were generalized or suppressed, particularly when the sensitive values in a group exhibit homogeneity.
In this scheme, the authors have taken a specific measurement called t-closeness which uses a characteristic that the distance of the sensitive values distribution in the original datasets and generalized datasets must be within threshold t.
After calculating the sensitive values of genes, we used the 5percentt as the cutoff value.
In our study, 167 datasets (labeled as M in the Formula below) in GEO were used to calculate the sensitive values of genes.
For example, prior knowledge can be modeled as knowledge of the sensitive values in a dataset that can then be used to eliminate candidate matches [ 59].
The most sensitive value of impulse oscillometry for RAO-affected horse evaluation, X5Hz was significantly different between RAO-affected horses and controls after challenge.
The l-diversity model handles a few of the weaknesses in the k-anonymity model in which protected identities to the level of k-individuals is not equal to protecting the corresponding sensitive values that were generalized or suppressed.
Probabilistic linking requires the readable sensitive values from different data stores to be brought together for similarity checking.
The extension of the privacy model from k-anonymity to l-diversity requires the integration of sensitive values into either the output keys or values of the mapper.
