localSupp2: Local Suppression 2
Description
An Algorithm to perfom local suppression to achieve k-anonymity.Usage
localSupp2(x, keyVars, w, importance=rep(1, length(keyVars)),
method="minimizeSupp", k=1)
Arguments
keyVars
column index of key variables
w
column index of sampling weights
importance
weights for each key variable
method
minimizeSupp (default), further methods will be included in future versions of the package
k
parameter for k-anonymity.
Value
- Object from class localSupp2.
- xAnonresulting data with suppressions
- suppsnumber of suppressions in the key variables
- totalSuppstotal number of suppressions.
- anonymityTRUE, if k-anonymity is achieved
- keyVarsindex of the key variables.
- importanceweight vector for key variables
- kk for k-anoymity
Details
With the help of this algorithm you can achieve k-anonymity in an optimized way. The procedure set missings only to those
key variables for which the importance is greater than 0. Key variables with higher importance will be prefered to be the variable which
will used for suppression of specific values, i.e. the vector of importance assign to each key variables a weight which is considered by
the algorithm.
To guarantee k-anonymity the wrapper of function localSupp2 should be applied (localSupp2Wrapper())
However, if the importance of some key variables are equal to zero,
the alorithm may not find a k-anonymity solution (because there isn't any solution
reachable at all, for example). The easiest way to overcome this
situation is to re-run the alorithm and allow for NA's in some more key variables,
i.e. re-run the algorithm with importance greater than
0 for all entries of importance.
This will result in k-anonymizated results and leads to only few suppressions
in the key variables where the importance of the variables are considered.
Method fastSupp avoids some calculation steps but this method is only significant
faster if there is a large data sets with few key variables.
However, fastSupp leads to an oversuppression (sligthly).References
Templ, M.
Statistical Disclosure Control for Microdata Using the R-Package sdcMicro,
Transactions on Data Privacy,
vol. 1, number 2, pp. 67-85, 2008.
http://www.tdp.cat/issues/abs.a004a08.phpExamples
Run this codeprint("this function is deprecated, please use localSuppression() instead")
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