Private anonymous data access

Ariel Hamlin; Rafail Ostrovsky; Mor Weiss; Daniel Wichs

doi:10.1007/978-3-030-17656-3_9

Private anonymous data access

Ariel Hamlin
, Rafail Ostrovsky
, Mor Weiss
, Daniel Wichs

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

14 Scopus citations

Abstract

We consider a scenario where a server holds a huge database that it wants to make accessible to a large group of clients. After an initial setup phase, clients should be able to read arbitrary locations in the database while maintaining privacy (the server does not learn which locations are being read) and anonymity (the server does not learn which client is performing each read). This should hold even if the server colludes with a subset of the clients. Moreover, the run-time of both the server and the client during each read operation should be low, ideally only poly-logarithmic in the size of the database and the number of clients. We call this notion Private Anonymous Data Access (PANDA). PANDA simultaneously combines aspects of Private Information Retrieval (PIR) and Oblivious RAM (ORAM). PIR has no initial setup, and allows anybody to privately and anonymously access a public database, but the server’s run-time is linear in the data size. On the other hand, ORAM achieves poly-logarithmic server run-time, but requires an initial setup after which only a single client with a secret key can access the database. The goal of PANDA is to get the best of both worlds: allow many clients to privately and anonymously access the database as in PIR, while having an efficient server as in ORAM. In this work, we construct bounded-collusion PANDA schemes, where the efficiency scales linearly with a bound on the number of corrupted clients that can collude with the server, but is otherwise poly-logarithmic in the data size and the total number of clients. Our solution relies on standard assumptions, namely the existence of fully homomorphic encryption, and combines techniques from both PIR and ORAM. We also extend PANDA to settings where clients can write to the database.

Original language	English
Title of host publication	Advances in Cryptology – EUROCRYPT 2019 - 38th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings
Editors	Yuval Ishai, Vincent Rijmen
Publisher	Springer Verlag
Pages	244-273
Number of pages	30
ISBN (Print)	9783030176556
DOIs	https://doi.org/10.1007/978-3-030-17656-3_9
State	Published - 2019
Externally published	Yes
Event	38th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Eurocrypt 2019 - Darmstadt, Germany Duration: 19 May 2019 → 23 May 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11477 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	38th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Eurocrypt 2019
Country/Territory	Germany
City	Darmstadt
Period	19/05/19 → 23/05/19

Bibliographical note

Publisher Copyright:
© International Association for Cryptologic Research 2019.

Funding

Acknowledgements. Rafail Ostrovsky is supported in part by NSF-BSF grant 1619348, DARPA SafeWare subcontract to Galois Inc., DARPA SPAWAR contract N66001-15-1C-4065, US-Israel BSF grant 2012366, OKAWA Foundation Research Award, IBM Faculty Research Award, Xerox Faculty Research Award, B. John Garrick Foundation Award, Teradata Research Award, and Lockheed-Martin Corporation Research Award. The views expressed are those of the authors and do not reflect position of the Department of Defense or the U.S. Government. Mor Weiss is supported in part by ISF grants 1861/16 and 1399/17, and AFOSR Award FA9550-17-1-0069. Daniel Wichs and Ariel Hamlin are supported by NSF grants CNS-1314722, CNS-1413964, CNS-1750795 and the Alfred P. Sloan Research Fellowship.

Funders	Funder number
Galois Inc.
NSF-BSF	1619348
US-Israel BSF	2012366
National Science Foundation	CNS-1750795, CNS-1413964, CNS-1314722
Air Force Office of Scientific Research	FA9550-17-1-0069
Defense Advanced Research Projects Agency	N66001-15-1C-4065
Alfred P. Sloan Foundation
International Business Machines Corporation
Iowa Science Foundation	1861/16, 1399/17

Access to Document

10.1007/978-3-030-17656-3_9

Cite this

Hamlin, A., Ostrovsky, R., Weiss, M., & Wichs, D. (2019). Private anonymous data access. In Y. Ishai, & V. Rijmen (Eds.), Advances in Cryptology – EUROCRYPT 2019 - 38th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings (pp. 244-273). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11477 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-17656-3_9

Hamlin, Ariel ; Ostrovsky, Rafail ; Weiss, Mor et al. / Private anonymous data access. Advances in Cryptology – EUROCRYPT 2019 - 38th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings. editor / Yuval Ishai ; Vincent Rijmen. Springer Verlag, 2019. pp. 244-273 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{4a21181e015a44ef8eb4b248a7c06ff8,

title = "Private anonymous data access",

abstract = "We consider a scenario where a server holds a huge database that it wants to make accessible to a large group of clients. After an initial setup phase, clients should be able to read arbitrary locations in the database while maintaining privacy (the server does not learn which locations are being read) and anonymity (the server does not learn which client is performing each read). This should hold even if the server colludes with a subset of the clients. Moreover, the run-time of both the server and the client during each read operation should be low, ideally only poly-logarithmic in the size of the database and the number of clients. We call this notion Private Anonymous Data Access (PANDA). PANDA simultaneously combines aspects of Private Information Retrieval (PIR) and Oblivious RAM (ORAM). PIR has no initial setup, and allows anybody to privately and anonymously access a public database, but the server{\textquoteright}s run-time is linear in the data size. On the other hand, ORAM achieves poly-logarithmic server run-time, but requires an initial setup after which only a single client with a secret key can access the database. The goal of PANDA is to get the best of both worlds: allow many clients to privately and anonymously access the database as in PIR, while having an efficient server as in ORAM. In this work, we construct bounded-collusion PANDA schemes, where the efficiency scales linearly with a bound on the number of corrupted clients that can collude with the server, but is otherwise poly-logarithmic in the data size and the total number of clients. Our solution relies on standard assumptions, namely the existence of fully homomorphic encryption, and combines techniques from both PIR and ORAM. We also extend PANDA to settings where clients can write to the database.",

author = "Ariel Hamlin and Rafail Ostrovsky and Mor Weiss and Daniel Wichs",

note = "Publisher Copyright: {\textcopyright} International Association for Cryptologic Research 2019.; 38th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Eurocrypt 2019 ; Conference date: 19-05-2019 Through 23-05-2019",

year = "2019",

doi = "10.1007/978-3-030-17656-3\_9",

language = "אנגלית",

isbn = "9783030176556",

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

publisher = "Springer Verlag",

pages = "244--273",

editor = "Yuval Ishai and Vincent Rijmen",

booktitle = "Advances in Cryptology – EUROCRYPT 2019 - 38th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings",

address = "גרמניה",

}

Hamlin, A, Ostrovsky, R, Weiss, M & Wichs, D 2019, Private anonymous data access. in Y Ishai & V Rijmen (eds), Advances in Cryptology – EUROCRYPT 2019 - 38th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11477 LNCS, Springer Verlag, pp. 244-273, 38th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Eurocrypt 2019, Darmstadt, Germany, 19/05/19. https://doi.org/10.1007/978-3-030-17656-3_9

Private anonymous data access. / Hamlin, Ariel; Ostrovsky, Rafail; Weiss, Mor et al.
Advances in Cryptology – EUROCRYPT 2019 - 38th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings. ed. / Yuval Ishai; Vincent Rijmen. Springer Verlag, 2019. p. 244-273 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11477 LNCS).

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

TY - GEN

T1 - Private anonymous data access

AU - Hamlin, Ariel

AU - Ostrovsky, Rafail

AU - Weiss, Mor

AU - Wichs, Daniel

PY - 2019

Y1 - 2019

N2 - We consider a scenario where a server holds a huge database that it wants to make accessible to a large group of clients. After an initial setup phase, clients should be able to read arbitrary locations in the database while maintaining privacy (the server does not learn which locations are being read) and anonymity (the server does not learn which client is performing each read). This should hold even if the server colludes with a subset of the clients. Moreover, the run-time of both the server and the client during each read operation should be low, ideally only poly-logarithmic in the size of the database and the number of clients. We call this notion Private Anonymous Data Access (PANDA). PANDA simultaneously combines aspects of Private Information Retrieval (PIR) and Oblivious RAM (ORAM). PIR has no initial setup, and allows anybody to privately and anonymously access a public database, but the server’s run-time is linear in the data size. On the other hand, ORAM achieves poly-logarithmic server run-time, but requires an initial setup after which only a single client with a secret key can access the database. The goal of PANDA is to get the best of both worlds: allow many clients to privately and anonymously access the database as in PIR, while having an efficient server as in ORAM. In this work, we construct bounded-collusion PANDA schemes, where the efficiency scales linearly with a bound on the number of corrupted clients that can collude with the server, but is otherwise poly-logarithmic in the data size and the total number of clients. Our solution relies on standard assumptions, namely the existence of fully homomorphic encryption, and combines techniques from both PIR and ORAM. We also extend PANDA to settings where clients can write to the database.

AB - We consider a scenario where a server holds a huge database that it wants to make accessible to a large group of clients. After an initial setup phase, clients should be able to read arbitrary locations in the database while maintaining privacy (the server does not learn which locations are being read) and anonymity (the server does not learn which client is performing each read). This should hold even if the server colludes with a subset of the clients. Moreover, the run-time of both the server and the client during each read operation should be low, ideally only poly-logarithmic in the size of the database and the number of clients. We call this notion Private Anonymous Data Access (PANDA). PANDA simultaneously combines aspects of Private Information Retrieval (PIR) and Oblivious RAM (ORAM). PIR has no initial setup, and allows anybody to privately and anonymously access a public database, but the server’s run-time is linear in the data size. On the other hand, ORAM achieves poly-logarithmic server run-time, but requires an initial setup after which only a single client with a secret key can access the database. The goal of PANDA is to get the best of both worlds: allow many clients to privately and anonymously access the database as in PIR, while having an efficient server as in ORAM. In this work, we construct bounded-collusion PANDA schemes, where the efficiency scales linearly with a bound on the number of corrupted clients that can collude with the server, but is otherwise poly-logarithmic in the data size and the total number of clients. Our solution relies on standard assumptions, namely the existence of fully homomorphic encryption, and combines techniques from both PIR and ORAM. We also extend PANDA to settings where clients can write to the database.

UR - https://www.scopus.com/pages/publications/85065885309

U2 - 10.1007/978-3-030-17656-3_9

DO - 10.1007/978-3-030-17656-3_9

M3 - ???researchoutput.researchoutputtypes.contributiontobookanthology.conference???

AN - SCOPUS:85065885309

SN - 9783030176556

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

SP - 244

EP - 273

BT - Advances in Cryptology – EUROCRYPT 2019 - 38th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings

A2 - Ishai, Yuval

A2 - Rijmen, Vincent

PB - Springer Verlag

T2 - 38th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Eurocrypt 2019

Y2 - 19 May 2019 through 23 May 2019

ER -

Hamlin A, Ostrovsky R, Weiss M, Wichs D. Private anonymous data access. In Ishai Y, Rijmen V, editors, Advances in Cryptology – EUROCRYPT 2019 - 38th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Proceedings. Springer Verlag. 2019. p. 244-273. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-17656-3_9

Private anonymous data access

Abstract

Publication series

Conference

Bibliographical note

Funding

Access to Document

Other files and links

Fingerprint

Cite this