Chameleon: A hybrid secure computation framework for machine learning applications

M. Sadegh Riazi; Ebrahim M. Songhori; Christian Weinert; Thomas Schneider; Oleksandr Tkachenko; Farinaz Koushanfar

doi:10.1145/3196494.3196522

Chameleon: A hybrid secure computation framework for machine learning applications

M. Sadegh Riazi, Ebrahim M. Songhori, Christian Weinert, Thomas Schneider, Oleksandr Tkachenko, Farinaz Koushanfar

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

Original language	English
Title of host publication	ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security
Publisher	Association for Computing Machinery, Inc
Pages	707-721
Number of pages	15
ISBN (Electronic)	9781450355766
DOIs	https://doi.org/10.1145/3196494.3196522
Publication status	Published - 29 May 2018
Externally published	Yes
Event	13th ACM Symposium on Information, Computer and Communications Security, ASIACCS 2018 - Incheon, Korea, Republic of Duration: 4 Jun 2018 → 8 Jun 2018

Publication series

Name	ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security

Conference

Conference	13th ACM Symposium on Information, Computer and Communications Security, ASIACCS 2018
Country/Territory	Korea, Republic of
City	Incheon
Period	4/06/18 → 8/06/18

Keywords

Deep Neural Networks
Garbled Circuits
Machine Learning
Secret Sharing
Secure Computation

Access to Document

10.1145/3196494.3196522

Cite this

Sadegh Riazi, M., Songhori, E. M., Weinert, C., Schneider, T., Tkachenko, O., & Koushanfar, F. (2018). Chameleon: A hybrid secure computation framework for machine learning applications. In ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security (pp. 707-721). (ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security). Association for Computing Machinery, Inc. https://doi.org/10.1145/3196494.3196522

Sadegh Riazi, M. ; Songhori, Ebrahim M. ; Weinert, Christian et al. / Chameleon : A hybrid secure computation framework for machine learning applications. ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security. Association for Computing Machinery, Inc, 2018. pp. 707-721 (ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security).

@inproceedings{4245b8e0626b485c825c55c6ac82aa3d,

title = "Chameleon: A hybrid secure computation framework for machine learning applications",

keywords = "Deep Neural Networks, Garbled Circuits, Machine Learning, Secret Sharing, Secure Computation",

author = "{Sadegh Riazi}, M. and Songhori, {Ebrahim M.} and Christian Weinert and Thomas Schneider and Oleksandr Tkachenko and Farinaz Koushanfar",

note = "Publisher Copyright: {\textcopyright} 2018 Association for Computing Machinery.; 13th ACM Symposium on Information, Computer and Communications Security, ASIACCS 2018 ; Conference date: 04-06-2018 Through 08-06-2018",

year = "2018",

month = may,

day = "29",

doi = "10.1145/3196494.3196522",

language = "English",

series = "ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security",

publisher = "Association for Computing Machinery, Inc",

pages = "707--721",

booktitle = "ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security",

}

Sadegh Riazi, M, Songhori, EM, Weinert, C, Schneider, T, Tkachenko, O & Koushanfar, F 2018, Chameleon: A hybrid secure computation framework for machine learning applications. in ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security. ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security, Association for Computing Machinery, Inc, pp. 707-721, 13th ACM Symposium on Information, Computer and Communications Security, ASIACCS 2018, Incheon, Korea, Republic of, 4/06/18. https://doi.org/10.1145/3196494.3196522

Chameleon: A hybrid secure computation framework for machine learning applications. / Sadegh Riazi, M.; Songhori, Ebrahim M.; Weinert, Christian et al.
ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security. Association for Computing Machinery, Inc, 2018. p. 707-721 (ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security).

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

TY - GEN

T1 - Chameleon

T2 - 13th ACM Symposium on Information, Computer and Communications Security, ASIACCS 2018

AU - Sadegh Riazi, M.

AU - Songhori, Ebrahim M.

AU - Weinert, Christian

AU - Schneider, Thomas

AU - Tkachenko, Oleksandr

AU - Koushanfar, Farinaz

PY - 2018/5/29

Y1 - 2018/5/29

KW - Deep Neural Networks

KW - Garbled Circuits

KW - Machine Learning

KW - Secret Sharing

KW - Secure Computation

UR - http://www.scopus.com/inward/record.url?scp=85049164871&partnerID=8YFLogxK

U2 - 10.1145/3196494.3196522

DO - 10.1145/3196494.3196522

M3 - Conference contribution

AN - SCOPUS:85049164871

T3 - ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security

SP - 707

EP - 721

BT - ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security

PB - Association for Computing Machinery, Inc

Y2 - 4 June 2018 through 8 June 2018

ER -

Sadegh Riazi M, Songhori EM, Weinert C, Schneider T, Tkachenko O, Koushanfar F. Chameleon: A hybrid secure computation framework for machine learning applications. In ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security. Association for Computing Machinery, Inc. 2018. p. 707-721. (ASIACCS 2018 - Proceedings of the 2018 ACM Asia Conference on Computer and Communications Security). doi: 10.1145/3196494.3196522

Chameleon: A hybrid secure computation framework for machine learning applications

Publication series

Conference

Keywords

Access to Document

Other files and links

Frameworks for Privacy-Preserving Machine Learning Inference

Cite this

Chameleon: A hybrid secure computation framework for machine learning applications

Publication series

Conference

Keywords

Access to Document

Other files and links

Activities

Frameworks for Privacy-Preserving Machine Learning Inference

Cite this