Let W be a string of length n over an alphabet Σ, k be a positive integer, and 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 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 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 (kn²) 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 (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.

Leibniz International Proceedings in Informatics
Annual Symposium on Combinatorial Pattern Matching
Evolutionary Intelligence

Bernardini, G., Loukides, G., Pissis, S., Sweering, M., Chen, H., Pisanti, N., & Stougie, L. (2020). String sanitization under edit distance. In Annual Symposium on Combinatorial Pattern Matching (pp. 7.1–7.14). doi:10.4230/LIPIcs.CPM.2020.7