K-Anonymity Versus PSI3 for Depersonalization and Security Assessment of Large Data Structures

DOI

https://doi.org/10.1007/978-3-031-37120-2_21
Final published version

Alexander Bogdanov
Nadezhda Shchegoleva
Valery Khvatov
Gennady Dik
Jasur Kiyamov
Aleksandr Dik

The article presents a modern approach to protecting personal data from de-anonymization. Descriptions of the k-anonymity model using entropy, with one-way publication of information, and the PSI3 technique using homomorphic encryption, with bilateral or multilateral information exchange, examples of the use of metrics for assessing the quality of depersonalization and their improvement, recommendations for using methods in the current activities of personal data operators are given.

Original language	English
Title of host publication	Computational Science and Its Applications - ICCSA 2023 Workshops
Subtitle of host publication	Athens, Greece, July 3–6, 2023, Proceedings, Part VI
Editors	Osvaldo Gervasi, Beniamino Murgante, Ana Maria A. C. Rocha, Chiara Garau, Francesco Scorza, Yeliz Karaca, Carmelo M. Torre
Place of Publication	Cham
Publisher	Springer Nature
Pages	317-333
Number of pages	17
ISBN (Print)	9783031371196
DOIs	https://doi.org/10.1007/978-3-031-37120-2_21
State	Published - 2023
Event	International Conference on Computational Science and Its Applications - Афины, Greece Duration: 3 Jul 2023 → 6 Jul 2023 Conference number: 23 https://iccsa.org/

Publication series

Name	LNCS
Volume	14109

Conference

Conference	International Conference on Computational Science and Its Applications
Abbreviated title	ICCSA 2023
Country/Territory	Greece
City	Афины
Period	3/07/23 → 6/07/23
Internet address	https://iccsa.org/

Research areas

information protection, personal data, k-anonymity, entropy, PSI3

ID: 107520966