CreateBalancedBF | R Documentation |
Creates CLKs with constant Hamming weights by adding a negated copy of the binary input vector which is then permutated.
CreateBalancedBF(ID, data, password)
ID |
A character vector or integer vector containing the IDs of the data.frame. |
data |
Bit vectors as created by any Bloom filter-based method. |
password |
a string used as a password for the random permutation. |
A data.frame containing IDs and the corresponding Balanced Bloom Filter.
Berger, J. M. (1961): A Note on Error Detection Codes for Asymmetric Channels. In: Information and Control 4: 68–73.
Knuth, Donald E. (1986): Efficient Balanced Codes. In: IEEE Transactions on Information Theory IT-32 (1): 51–53.
Schnell, R., Borgs, C. (2016): Randomized Response and Balanced Bloom Filters for Privacy Preserving Record Linkage. IEEE International Conference on Data Mining (ICDM 2016), Barcelona.
CreateBF
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CreateBitFlippingBF
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CreateCLK
,
CreateDoubleBalancedBF
,
CreateEnsembleCLK
,
CreateMarkovCLK
,
CreateRecordLevelBF
,
StandardizeString
# Load test data testFile <- file.path(path.package("PPRL"), "extdata/testdata.csv") testData <- read.csv(testFile, head = FALSE, sep = "\t", colClasses = "character") # Create bit vectors e.g. with CreateBF testData <- CreateBF(ID = testData$V1, testData$V7, k = 20, padding = 1, q = 2, l = 1000, password = "(H]$6Uh*-Z204q") # Create Balanced Bloom Filters BB <- CreateBalancedBF(ID = testData$ID, data = testData$CLKs, password = "hdayfkgh")
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