Title | A critique of the sensitivity rules usually employed for statistical table protection |

Publication Type | Journal Article |

Year of Publication | 2002 |

Authors | Domingo-Ferrer J [1], Torra V [2] |

Journal | Int. J. of Unc., Fuzziness and Knowledge Based Systems |

Volume | 10 |

Abstract | In statistical disclosure control of tabular data, sensitivity rules are commonly used to decide whether a table cell is sensitive and should therefore not be published. The most popular sensitivity rules are the dominance rule, the $p%$-rule and the $pq$-rule. The dominance rule has received critiques based on specific numerical examples and is being gradually abandoned by leading statistical agencies. In this paper, we construct general counterexamples which show that {\em none} of the above rules does adequately reflect disclosure risk if cell contributors or coalitions of them behave as intruders: in that case, releasing a cell declared non-sensitive can imply higher disclosure risk than releasing a cell declared sensitive. As possible solutions, we propose an alternative sensitivity rule based on the concentration of relative contributions. More generally, we suggest to complement {\em a priori} risk assessment based on sensitivity rules with {\em a posteriori} risk assessment which takes into account tables after they have been protected. |