From Isolation to Identification

Giuseppe D’Acquisto; Aloni Cohen; Maurizio Naldi; Kobbi Nissim

doi:10.1007/978-3-031-69651-0_1

From Isolation to Identification

Giuseppe D’Acquisto, Aloni Cohen, Maurizio Naldi, Kobbi Nissim

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We present a mathematical framework for understanding when successfully distinguishing a person from all other persons in a data set—a phenomenon which we call isolation—may enable identification, a notion which is central to deciding whether a release based on the data set is subject to data protection regulation. We show that a baseline degree of isolation is unavoidable in the sense that isolation can typically happen with high probability even before a release was made about the data set and hence identification is not enabled. We then describe settings where isolation resulting from a data release may enable identification.

Original language	English
Title of host publication	Privacy in Statistical Databases - International Conference, PSD 2024, Proceedings
Editors	Josep Domingo-Ferrer, Melek Önen
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	3-17
Number of pages	15
ISBN (Print)	9783031696503
DOIs	https://doi.org/10.1007/978-3-031-69651-0_1
State	Published - 1 Jan 2024
Externally published	Yes
Event	International Conference on Privacy in Statistical Databases, PSD 2024 - Antibes Juan-les-Pins, France Duration: 25 Sep 2024 → 27 Sep 2024

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14915 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Privacy in Statistical Databases, PSD 2024
Country/Territory	France
City	Antibes Juan-les-Pins
Period	25/09/24 → 27/09/24

Keywords

data protection
identification
isolation
privacy

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-031-69651-0_1

Cite this

D’Acquisto, G., Cohen, A., Naldi, M., & Nissim, K. (2024). From Isolation to Identification. In J. Domingo-Ferrer, & M. Önen (Eds.), Privacy in Statistical Databases - International Conference, PSD 2024, Proceedings (pp. 3-17). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14915 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-69651-0_1

D’Acquisto, Giuseppe ; Cohen, Aloni ; Naldi, Maurizio et al. / From Isolation to Identification. Privacy in Statistical Databases - International Conference, PSD 2024, Proceedings. editor / Josep Domingo-Ferrer ; Melek Önen. Springer Science and Business Media Deutschland GmbH, 2024. pp. 3-17 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{259497efabaf4e9a86e863f54bddea23,

title = "From Isolation to Identification",

abstract = "We present a mathematical framework for understanding when successfully distinguishing a person from all other persons in a data set—a phenomenon which we call isolation—may enable identification, a notion which is central to deciding whether a release based on the data set is subject to data protection regulation. We show that a baseline degree of isolation is unavoidable in the sense that isolation can typically happen with high probability even before a release was made about the data set and hence identification is not enabled. We then describe settings where isolation resulting from a data release may enable identification.",

keywords = "data protection, identification, isolation, privacy",

author = "Giuseppe D{\textquoteright}Acquisto and Aloni Cohen and Maurizio Naldi and Kobbi Nissim",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; International Conference on Privacy in Statistical Databases, PSD 2024 ; Conference date: 25-09-2024 Through 27-09-2024",

year = "2024",

month = jan,

day = "1",

doi = "10.1007/978-3-031-69651-0_1",

language = "English",

isbn = "9783031696503",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "3--17",

editor = "Josep Domingo-Ferrer and Melek {\"O}nen",

booktitle = "Privacy in Statistical Databases - International Conference, PSD 2024, Proceedings",

address = "Germany",

}

D’Acquisto, G, Cohen, A, Naldi, M & Nissim, K 2024, From Isolation to Identification. in J Domingo-Ferrer & M Önen (eds), Privacy in Statistical Databases - International Conference, PSD 2024, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14915 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 3-17, International Conference on Privacy in Statistical Databases, PSD 2024, Antibes Juan-les-Pins, France, 25/09/24. https://doi.org/10.1007/978-3-031-69651-0_1

From Isolation to Identification. / D’Acquisto, Giuseppe; Cohen, Aloni; Naldi, Maurizio et al.
Privacy in Statistical Databases - International Conference, PSD 2024, Proceedings. ed. / Josep Domingo-Ferrer; Melek Önen. Springer Science and Business Media Deutschland GmbH, 2024. p. 3-17 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14915 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - From Isolation to Identification

AU - D’Acquisto, Giuseppe

AU - Cohen, Aloni

AU - Naldi, Maurizio

AU - Nissim, Kobbi

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

PY - 2024/1/1

Y1 - 2024/1/1

N2 - We present a mathematical framework for understanding when successfully distinguishing a person from all other persons in a data set—a phenomenon which we call isolation—may enable identification, a notion which is central to deciding whether a release based on the data set is subject to data protection regulation. We show that a baseline degree of isolation is unavoidable in the sense that isolation can typically happen with high probability even before a release was made about the data set and hence identification is not enabled. We then describe settings where isolation resulting from a data release may enable identification.

AB - We present a mathematical framework for understanding when successfully distinguishing a person from all other persons in a data set—a phenomenon which we call isolation—may enable identification, a notion which is central to deciding whether a release based on the data set is subject to data protection regulation. We show that a baseline degree of isolation is unavoidable in the sense that isolation can typically happen with high probability even before a release was made about the data set and hence identification is not enabled. We then describe settings where isolation resulting from a data release may enable identification.

KW - data protection

KW - identification

KW - isolation

KW - privacy

UR - http://www.scopus.com/inward/record.url?scp=85205130552&partnerID=8YFLogxK

U2 - 10.1007/978-3-031-69651-0_1

DO - 10.1007/978-3-031-69651-0_1

M3 - Conference contribution

AN - SCOPUS:85205130552

SN - 9783031696503

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 3

EP - 17

BT - Privacy in Statistical Databases - International Conference, PSD 2024, Proceedings

A2 - Domingo-Ferrer, Josep

A2 - Önen, Melek

PB - Springer Science and Business Media Deutschland GmbH

T2 - International Conference on Privacy in Statistical Databases, PSD 2024

Y2 - 25 September 2024 through 27 September 2024

ER -

D’Acquisto G, Cohen A, Naldi M, Nissim K. From Isolation to Identification. In Domingo-Ferrer J, Önen M, editors, Privacy in Statistical Databases - International Conference, PSD 2024, Proceedings. Springer Science and Business Media Deutschland GmbH. 2024. p. 3-17. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-69651-0_1