An empirical study of differentially-private analytics for high-speed network data

Oana Georgiana Niculaescu; Gabriel Ghinita

doi:10.1145/3176258.3176944

An empirical study of differentially-private analytics for high-speed network data

Oana Georgiana Niculaescu
, Gabriel Ghinita

Computer Science

University of Massachusetts Boston

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

Original language	English
Title of host publication	CODASPY 2018 - Proceedings of the 8th ACM Conference on Data and Application Security and Privacy
Publisher	Association for Computing Machinery, Inc
Pages	149-151
Number of pages	3
ISBN (Electronic)	9781450356329
DOIs	https://doi.org/10.1145/3176258.3176944
State	Published - Mar 13 2018
Event	8th ACM Conference on Data and Application Security and Privacy, CODASPY 2018 - Tempe, United States Duration: Mar 19 2018 → Mar 21 2018

Publication series

Name	CODASPY 2018 - Proceedings of the 8th ACM Conference on Data and Application Security and Privacy
Volume	2018-January

Conference

Conference	8th ACM Conference on Data and Application Security and Privacy, CODASPY 2018
Country/Territory	United States
City	Tempe
Period	3/19/18 → 3/21/18

ASJC Scopus Subject Areas

Computer Science Applications
Information Systems
Software

Access to Document

10.1145/3176258.3176944

Cite this

Niculaescu, O. G., & Ghinita, G. (2018). An empirical study of differentially-private analytics for high-speed network data. In CODASPY 2018 - Proceedings of the 8th ACM Conference on Data and Application Security and Privacy (pp. 149-151). (CODASPY 2018 - Proceedings of the 8th ACM Conference on Data and Application Security and Privacy; Vol. 2018-January). Association for Computing Machinery, Inc. https://doi.org/10.1145/3176258.3176944

An empirical study of differentially-private analytics for high-speed network data. / Niculaescu, Oana Georgiana; Ghinita, Gabriel.
CODASPY 2018 - Proceedings of the 8th ACM Conference on Data and Application Security and Privacy. Association for Computing Machinery, Inc, 2018. p. 149-151 (CODASPY 2018 - Proceedings of the 8th ACM Conference on Data and Application Security and Privacy; Vol. 2018-January).

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

Niculaescu, OG & Ghinita, G 2018, An empirical study of differentially-private analytics for high-speed network data. in CODASPY 2018 - Proceedings of the 8th ACM Conference on Data and Application Security and Privacy. CODASPY 2018 - Proceedings of the 8th ACM Conference on Data and Application Security and Privacy, vol. 2018-January, Association for Computing Machinery, Inc, pp. 149-151, 8th ACM Conference on Data and Application Security and Privacy, CODASPY 2018, Tempe, United States, 3/19/18. https://doi.org/10.1145/3176258.3176944

Niculaescu OG, Ghinita G. An empirical study of differentially-private analytics for high-speed network data. In CODASPY 2018 - Proceedings of the 8th ACM Conference on Data and Application Security and Privacy. Association for Computing Machinery, Inc. 2018. p. 149-151. (CODASPY 2018 - Proceedings of the 8th ACM Conference on Data and Application Security and Privacy). doi: 10.1145/3176258.3176944

Niculaescu, Oana Georgiana ; Ghinita, Gabriel. / An empirical study of differentially-private analytics for high-speed network data. CODASPY 2018 - Proceedings of the 8th ACM Conference on Data and Application Security and Privacy. Association for Computing Machinery, Inc, 2018. pp. 149-151 (CODASPY 2018 - Proceedings of the 8th ACM Conference on Data and Application Security and Privacy).

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An empirical study of differentially-private analytics for high-speed network data

Publication series

Conference

ASJC Scopus Subject Areas

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