An Efficient Toolkit for Computing Private Set Operations. / Davidson, Alexander; Cid, Carlos.

Information Security and Privacy: 22nd Australasian Conference, ACISP 2017, Auckland, New Zealand, July 3–5, 2017, Proceedings, Part II. ed. / Josef Pieprzyk; Suriadi Suriadi. Vol. 2 Springer Heidelberg, 2017. p. 261-278 (Lecture Notes in Computer Science; Vol. 10343).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Published

Standard

An Efficient Toolkit for Computing Private Set Operations. / Davidson, Alexander; Cid, Carlos.

Information Security and Privacy: 22nd Australasian Conference, ACISP 2017, Auckland, New Zealand, July 3–5, 2017, Proceedings, Part II. ed. / Josef Pieprzyk; Suriadi Suriadi. Vol. 2 Springer Heidelberg, 2017. p. 261-278 (Lecture Notes in Computer Science; Vol. 10343).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Davidson, A & Cid, C 2017, An Efficient Toolkit for Computing Private Set Operations. in J Pieprzyk & S Suriadi (eds), Information Security and Privacy: 22nd Australasian Conference, ACISP 2017, Auckland, New Zealand, July 3–5, 2017, Proceedings, Part II. vol. 2, Lecture Notes in Computer Science, vol. 10343, Springer Heidelberg, pp. 261-278, ACISP 2017 - 22nd Australasian Conference on Information Security and Privacy, Auckland, New Zealand, 3/07/17. https://doi.org/10.1007/978-3-319-59870-3_15

APA

Davidson, A., & Cid, C. (2017). An Efficient Toolkit for Computing Private Set Operations. In J. Pieprzyk, & S. Suriadi (Eds.), Information Security and Privacy: 22nd Australasian Conference, ACISP 2017, Auckland, New Zealand, July 3–5, 2017, Proceedings, Part II (Vol. 2, pp. 261-278). (Lecture Notes in Computer Science; Vol. 10343). Springer Heidelberg. https://doi.org/10.1007/978-3-319-59870-3_15

Vancouver

Davidson A, Cid C. An Efficient Toolkit for Computing Private Set Operations. In Pieprzyk J, Suriadi S, editors, Information Security and Privacy: 22nd Australasian Conference, ACISP 2017, Auckland, New Zealand, July 3–5, 2017, Proceedings, Part II. Vol. 2. Springer Heidelberg. 2017. p. 261-278. (Lecture Notes in Computer Science). https://doi.org/10.1007/978-3-319-59870-3_15

Author

Davidson, Alexander ; Cid, Carlos. / An Efficient Toolkit for Computing Private Set Operations. Information Security and Privacy: 22nd Australasian Conference, ACISP 2017, Auckland, New Zealand, July 3–5, 2017, Proceedings, Part II. editor / Josef Pieprzyk ; Suriadi Suriadi. Vol. 2 Springer Heidelberg, 2017. pp. 261-278 (Lecture Notes in Computer Science).

BibTeX

@inproceedings{42ca65cb031147289dc17592d12a0060,
title = "An Efficient Toolkit for Computing Private Set Operations",
abstract = "Private set operation (PSO) protocols provide a natural way of securely performing operations on data sets, such that crucial details of the input sets are not revealed. Such protocols have an ever-increasing number of practical applications, particularly when implementing privacy-preserving data mining schemes. Protocols for computing private set operations have been prevalent in multi-party computation literature over the past decade, and in the case of private set intersection (PSI), have become practically feasible to run in real applications. In contrast, other set operations such as union have received less attention from the research community, and the few existing designs are often limited in their feasibility. In this work we aim to fill this gap, and present a new technique using Bloom filter data structures and additive homomorphic encryption to develop the first private set union protocol with both linear computation and communication complexities. Moreover, we show how to adapt this protocol to give novel ways of computing PSI and private set intersection/union cardinality with only minor changes to the protocol computation. Our work resembles therefore a toolkit for scalable private set computation with linear complexities, and we provide a thorough experimental analysis that shows that the online phase of our designs is practical up to large set sizes.",
author = "Alexander Davidson and Carlos Cid",
year = "2017",
doi = "10.1007/978-3-319-59870-3_15",
language = "English",
isbn = "978-3-319-59869-7",
volume = "2",
series = "Lecture Notes in Computer Science",
publisher = "Springer Heidelberg",
pages = "261--278",
editor = "Josef Pieprzyk and Suriadi Suriadi",
booktitle = "Information Security and Privacy",
address = "Germany",
note = "ACISP 2017 - 22nd Australasian Conference on Information Security and Privacy ; Conference date: 03-07-2017 Through 05-07-2017",
url = "http://acisp.massey.ac.nz/",

}

RIS

TY - GEN

T1 - An Efficient Toolkit for Computing Private Set Operations

AU - Davidson, Alexander

AU - Cid, Carlos

PY - 2017

Y1 - 2017

N2 - Private set operation (PSO) protocols provide a natural way of securely performing operations on data sets, such that crucial details of the input sets are not revealed. Such protocols have an ever-increasing number of practical applications, particularly when implementing privacy-preserving data mining schemes. Protocols for computing private set operations have been prevalent in multi-party computation literature over the past decade, and in the case of private set intersection (PSI), have become practically feasible to run in real applications. In contrast, other set operations such as union have received less attention from the research community, and the few existing designs are often limited in their feasibility. In this work we aim to fill this gap, and present a new technique using Bloom filter data structures and additive homomorphic encryption to develop the first private set union protocol with both linear computation and communication complexities. Moreover, we show how to adapt this protocol to give novel ways of computing PSI and private set intersection/union cardinality with only minor changes to the protocol computation. Our work resembles therefore a toolkit for scalable private set computation with linear complexities, and we provide a thorough experimental analysis that shows that the online phase of our designs is practical up to large set sizes.

AB - Private set operation (PSO) protocols provide a natural way of securely performing operations on data sets, such that crucial details of the input sets are not revealed. Such protocols have an ever-increasing number of practical applications, particularly when implementing privacy-preserving data mining schemes. Protocols for computing private set operations have been prevalent in multi-party computation literature over the past decade, and in the case of private set intersection (PSI), have become practically feasible to run in real applications. In contrast, other set operations such as union have received less attention from the research community, and the few existing designs are often limited in their feasibility. In this work we aim to fill this gap, and present a new technique using Bloom filter data structures and additive homomorphic encryption to develop the first private set union protocol with both linear computation and communication complexities. Moreover, we show how to adapt this protocol to give novel ways of computing PSI and private set intersection/union cardinality with only minor changes to the protocol computation. Our work resembles therefore a toolkit for scalable private set computation with linear complexities, and we provide a thorough experimental analysis that shows that the online phase of our designs is practical up to large set sizes.

U2 - 10.1007/978-3-319-59870-3_15

DO - 10.1007/978-3-319-59870-3_15

M3 - Conference contribution

SN - 978-3-319-59869-7

VL - 2

T3 - Lecture Notes in Computer Science

SP - 261

EP - 278

BT - Information Security and Privacy

A2 - Pieprzyk, Josef

A2 - Suriadi, Suriadi

PB - Springer Heidelberg

T2 - ACISP 2017 - 22nd Australasian Conference on Information Security and Privacy

Y2 - 3 July 2017 through 5 July 2017

ER -