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On String and Graph Sanitization

Authors Giulia Bernardini , Huiping Chen , Grigorios Loukides , Solon P. Pissis

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Subject Classification

ACM Subject Classification
  • Theory of computation → Pattern matching
Keywords
  • data privacy
  • data sanitization
  • string algorithms
  • graph algorithms

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Abstract

Data sanitization is a process that conceals sensitive patterns from a given dataset. A secondary goal is to not severely harm the utility of the underlying data along this process. We survey some recent advancements on two related data sanitization topics: string and graph sanitization. In particular, we highlight the important contributions of our friend Prof. Roberto Grossi along this journey.

Cite As Get BibTex

Giulia Bernardini, Huiping Chen, Grigorios Loukides, and Solon P. Pissis. On String and Graph Sanitization. In From Strings to Graphs, and Back Again: A Festschrift for Roberto Grossi's 60th Birthday. Open Access Series in Informatics (OASIcs), Volume 132, pp. 9:1-9:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/OASIcs.Grossi.9

Author Details

Giulia Bernardini
  • University of Milan, Italy
Huiping Chen
  • University of Birmingham, UK
Grigorios Loukides
  • King’s College London, UK
Solon P. Pissis
  • CWI, Amsterdam, The Netherlands
  • Vrije Universiteit, Amsterdam, The Netherlands

Funding

  • Bernardini, Giulia: Member of the Gruppo Nazionale Calcolo Scientifico-Istituto Nazionale di Alta Matematica (GNCS-INdAM).
  • Pissis, Solon P.: Supported in part by the PANGAIA and ALPACA projects that have received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreements No 872539 and 956229, respectively.

Acknowledgements

We want to thank Prof. Roberto Grossi for this journey (and more). We would also like to thank the editors for providing us with the opportunity and pleasure to write this paper.

References

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