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Communication Dans Un Congrès Année : 2020

String Sanitization Under Edit Distance

Résumé

Let W be a string of length n over an alphabet Σ, k be a positive integer, and S be a set of length-k substrings of W. The ETFS problem asks us to construct a string X ED such that: (i) no string of S occurs in X ED ; (ii) the order of all other length-k substrings over Σ is the same in W and in X ED ; and (iii) X ED has minimal edit distance to W. When W represents an individual's data and S represents a set of confidential substrings, algorithms solving ETFS can be applied for utility-preserving string sanitization [Bernardini et al., ECML PKDD 2019]. Our first result here is an algorithm to solve ETFS in O(kn 2) time, which improves on the state of the art [Bernardini et al., arXiv 2019] by a factor of |Σ|. Our algorithm is based on a non-trivial modification of the classic dynamic programming algorithm for computing the edit distance between two strings. Notably, we also show that ETFS cannot be solved in O(n 2−δ) time, for any δ > 0, unless the strong exponential time hypothesis is false. To achieve this, we reduce the edit distance problem, which is known to admit the same conditional lower bound [Bringmann and Künnemann, FOCS 2015], to ETFS.
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Dates et versions

hal-02957647 , version 1 (05-10-2020)

Identifiants

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Giulia Bernardini, Huiping Chen, Grigorios Loukides, Nadia Pisanti, Solon P Pissis, et al.. String Sanitization Under Edit Distance. CPM 2020 - 31st Annual Symposium on Combinatorial Pattern Matching, Jun 2020, Copenhagen, Denmark. pp.1-14, ⟨10.4230/LIPIcs.CPM.2020.7⟩. ⟨hal-02957647⟩

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