Abstract
Data masking is a common technique for sanitizing sensitive data maintained in database systems, and it is also becoming increasingly important in various application areas, such as in record linkage of personal data. This work formalizes the Pattern Masking for Dictionary Matching (PMDM) problem. In PMDM, we are given a dictionary D of d strings, each of length ℓ, a query string q of length ℓ, and a positive integer z, and we are asked to compute a smallest set K ⊆ {1, . . ., ℓ}, so that if q[i] is replaced by a wildcard for all i ∈ K, then q matches at least z strings from D. Solving PMDM allows providing data utility guarantees as opposed to existing approaches.
We first show, through a reduction from the well-known k-Clique problem, that a decision version of the PMDM problem is NP-complete, even for strings over a binary alphabet. We thus approach the problem from a more practical perspective. We show a combinatorial O((dℓ)|K|/3 + dℓ)-time and O(dℓ)-space algorithm for PMDM for |K| = O(1). In fact, we show that we cannot hope for a faster combinatorial algorithm, unless the combinatorial k-Clique hypothesis fails [Abboud et al., SIAM J. Comput. 2018; Lincoln et al., SODA 2018]. We also generalize this algorithm for the problem of masking multiple query strings simultaneously so that every string has at least z matches in D.
Note that PMDM can be viewed as a generalization of the decision version of the dictionary matching with mismatches problem: by querying a PMDM data structure with string q and z = 1, one obtains the minimal number of mismatches of q with any string from D. The query time or space of all known data structures for the more restricted problem of dictionary matching with at most k mismatches incurs some exponential factor with respect to k. A simple exact algorithm for PMDM runs in time O(2ℓd).
We present a data structure for PMDM that answers queries over D in time O(2ℓ/2(2ℓ/2 + τ)ℓ) and requires space O(2ℓd2/τ2 + 2ℓ/2d), for any parameter τ ∈ [1, d]. We complement our results by showing a two-way polynomial-time reduction between PMDM and the Minimum Union problem [Chlamtáč et al., SODA 2017]. This gives a polynomial-time O(d1/4+ϵ)approximation algorithm for PMDM, which is tight under a plausible complexity conjecture.
Original language | English |
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Title of host publication | 32nd International Symposium on Algorithms and Computation (ISAAC 2021) |
Editors | Hee-Kap Ahn, Kunihiko Sadakane |
Publisher | Schloss Dagstuhl |
Number of pages | 19 |
ISBN (Electronic) | 9783959772143 |
DOIs | |
Publication status | Published - 30 Nov 2021 |
Event | 32nd International Symposium on Algorithms and Computation, ISAAC 2021 - Fukuoka, Japan Duration: 6 Dec 2021 → 8 Dec 2021 |
Publication series
Name | Leibniz International Proceedings in Informatics (LIPIcs) |
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Publisher | Schloss Dagstuhl |
Volume | 212 |
ISSN (Electronic) | 1868-8969 |
Conference
Conference | 32nd International Symposium on Algorithms and Computation, ISAAC 2021 |
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Country/Territory | Japan |
City | Fukuoka |
Period | 6/12/21 → 8/12/21 |
Bibliographical note
Funding Information:Funding This paper is part of the PANGAIA project that has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 872539. This paper is also part of the ALPACA project that has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 956229. Panagiotis Charalampopoulos: Supported by the Israel Science Foundation grant 592/17. Huiping Chen: Supported by a CSC Scholarship. Grigorios Loukides: Supported in part by the Leverhulme Trust RPG-2019-399 project. Nadia Pisanti: Supported by the University of Pisa under the “PRA – Progetti di Ricerca di Ateneo” (Institutional Research Grants) – Project no. PRA_2020-2021_26. Jakub Radoszewski: Supported by the Polish National Science Center, grant number 2018/31/D/ST6/03991.
Publisher Copyright:
© Panagiotis Charalampopoulos, Huiping Chen, Peter Christen, Grigorios Loukides, Nadia Pisanti, Solon P. Pissis, and Jakub Radoszewski.
Keywords
- Dictionary matching
- Query term dropping
- Record linkage
- String algorithms
- Wildcards
ASJC Scopus subject areas
- Software