Package: dominoise
Title: Parsimonious Noise Perturbation for Magnitude Tables
Version: 0.2.0
Authors@R: c(
    person("Julien", "Jamme", email = "julien.jamme@insee.fr",
           role = c("aut", "cre"), 
           comment = c(ORCID = "0009-0009-9054-7053")),
    person("Institut national de la statistique et des études économiques",
           role = "cph"))
Description: Protects magnitude tables, such as tables of enterprise turnover,
    by multiplying each total by a Gaussian noise combining a dominance-driven
    component and a general-purpose one, governed by three parameters only.
    Information loss and disclosure risks for three attack scenarios
    (external inference, internal inference and differencing) are available in
    closed form, so that calibration requires neither simulation nor
    re-estimation on the data. The package guides that calibration
    step by step, from the differencing noise to the dominance parameters,
    with decision tables and risk-utility plots, applies the mechanism to an
    aggregated table using SHA-512 hashed random keys for consistency over
    time, and reports the risk and utility actually achieved. The method is
    described in Jamme (2027)
    <doi:10.1007/978-3-032-37883-5_9>.
License: GPL (>= 3)
URL: https://github.com/InseeFrLab/dominoise,
        https://inseefrlab.github.io/dominoise/
BugReports: https://github.com/InseeFrLab/dominoise/issues
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1)
Imports: stats, utils, digest, assertthat, rlang
Suggests: ggplot2 (>= 3.5.0), testthat (>= 3.0.0)
RoxygenNote: 8.0.0
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-10-04 09:54:16 UTC; onyxia
Author: Julien Jamme [aut, cre] (ORCID:
    <https://orcid.org/0009-0009-9054-7053>),
  Institut national de la statistique et des études économiques [cph]
Maintainer: Julien Jamme <julien.jamme@insee.fr>
Repository: CRAN
Date/Publication: 2026-10-15 16:20:02 UTC
