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Private Lives Matter: A Differential Private Functional Encryption Scheme

Authors:

Alexandros Bakas,

Antonis Michalas,

Tassos DimitriouAuthors Info & Claims

CODASPY '22: Proceedings of the Twelfth ACM Conference on Data and Application Security and Privacy

Pages 300 - 311

https://doi.org/10.1145/3508398.3511514

Published: 15 April 2022 Publication History

Abstract

The use of data combined with tailored statistical analysis has presented a unique opportunity to organizations in diverse fields to observe users' behaviors and needs, and accordingly adapt and fine-tune their services. However, in order to offer utilizable, plausible, and personalized alternatives to users, this process usually also entails a breach of their privacy. The use of statistical databases for releasing data analytics is growing exponentially, and while many cryptographic methods are utilized to protect the confidentiality of the data -- a task that has been ably carried out by many authors over the years -- only a few %rudimentary number of works focus on the problem of privatizing the actual databases. Believing that securing and privatizing databases are two equilateral problems, in this paper, we propose a hybrid approach by combining Functional Encryption with the principles of Differential Privacy. Our main goal is not only to design a scheme for processing statistical data and releasing statistics in a privacy-preserving way but also to provide a richer, more balanced, and comprehensive approach in which data analytics and cryptography go hand in hand with a shift towards increased privacy.

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Cited By

Nuoskala CRabbaninejad RDimitriou TMichalas ANiu JVaidya J(2024)FE[r]Chain: Enforcing Fairness in Blockchain Data Exchanges Through Verifiable Functional EncryptionProceedings of the 29th ACM Symposium on Access Control Models and Technologies10.1145/3649158.3657049(183-191)Online publication date: 24-Jun-2024
https://dl.acm.org/doi/10.1145/3649158.3657049
Bouleghlimat IBoudouda SHacini S(2024)LSPP: a leakage-resilient security approach for a cloud-assisted big dataThe Journal of Supercomputing10.1007/s11227-024-06657-x81:1Online publication date: 12-Nov-2024
https://doi.org/10.1007/s11227-024-06657-x
Nguyen KKhan TMichalas A(2024)Split Without a Leak: Reducing Privacy Leakage in Split LearningSecurity and Privacy in Communication Networks10.1007/978-3-031-64954-7_17(321-344)Online publication date: 15-Oct-2024
https://doi.org/10.1007/978-3-031-64954-7_17
Show More Cited By

Index Terms

Private Lives Matter: A Differential Private Functional Encryption Scheme
1. Security and privacy

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cover image ACM Conferences

CODASPY '22: Proceedings of the Twelfth ACM Conference on Data and Application Security and Privacy

April 2022

392 pages

ISBN:9781450392204

DOI:10.1145/3508398

General Chair:
Anupam Joshi
University of Maryland, Baltimore County, USA
,
Program Chairs:
Maribel Fernandez
King's College London, UK
,
Rakesh M. Verma
University of Houston, USA

Copyright © 2022 ACM.

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Published: 15 April 2022

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CODASPY '22

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SIGSAC

CODASPY '22: Twelveth ACM Conference on Data and Application Security and Privacy

April 24 - 27, 2022

MD, Baltimore, USA

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Overall Acceptance Rate 149 of 789 submissions, 19%

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Cited By

Nuoskala CRabbaninejad RDimitriou TMichalas ANiu JVaidya J(2024)FE[r]Chain: Enforcing Fairness in Blockchain Data Exchanges Through Verifiable Functional EncryptionProceedings of the 29th ACM Symposium on Access Control Models and Technologies10.1145/3649158.3657049(183-191)Online publication date: 24-Jun-2024
https://dl.acm.org/doi/10.1145/3649158.3657049
Bouleghlimat IBoudouda SHacini S(2024)LSPP: a leakage-resilient security approach for a cloud-assisted big dataThe Journal of Supercomputing10.1007/s11227-024-06657-x81:1Online publication date: 12-Nov-2024
https://doi.org/10.1007/s11227-024-06657-x
Nguyen KKhan TMichalas A(2024)Split Without a Leak: Reducing Privacy Leakage in Split LearningSecurity and Privacy in Communication Networks10.1007/978-3-031-64954-7_17(321-344)Online publication date: 15-Oct-2024
https://doi.org/10.1007/978-3-031-64954-7_17
Rabaninejad RBakas AFrimpong EMichalas A(2023)A Secure Bandwidth-Efficient Treatment for Dropout-Resistant Time-Series Data Aggregation2023 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops56833.2023.10150348(640-645)Online publication date: 13-Mar-2023
https://doi.org/10.1109/PerComWorkshops56833.2023.10150348
Bakas AFrimpong EMichalas A(2023)Symmetrical Disguise: Realizing Homomorphic Encryption Services from Symmetric PrimitivesSecurity and Privacy in Communication Networks10.1007/978-3-031-25538-0_19(353-370)Online publication date: 4-Feb-2023
https://doi.org/10.1007/978-3-031-25538-0_19
Bakas AMichalas AFrimpong ERabaninejad R(2022)Feel the Quantum Functioning: Instantiating Generic Multi-Input Functional Encryption from Learning with ErrorsData and Applications Security and Privacy XXXVI10.1007/978-3-031-10684-2_16(279-299)Online publication date: 18-Jul-2022
https://dl.acm.org/doi/10.1007/978-3-031-10684-2_16

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