Eluding Secure Aggregation in Federated Learning via Model Inconsistency

Dario Pasquini; Danilo Francati; Giuseppe Ateniese

doi:10.1145/3548606.3560557

Eluding Secure Aggregation in Federated Learning via Model Inconsistency

Dario Pasquini
, Danilo Francati
, Giuseppe Ateniese

Department of Information Security

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

Original language	English
Title of host publication	CCS 2022 - Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security
Publisher	Association for Computing Machinery (ACM)
Pages	2429-2443
Number of pages	15
ISBN (Electronic)	9781450394505
DOIs	https://doi.org/10.1145/3548606.3560557
Publication status	Published - 7 Nov 2022
Event	28th ACM SIGSAC Conference on Computer and Communications Security, CCS 2022 - Los Angeles, United States Duration: 7 Nov 2022 → 11 Nov 2022

Publication series

Name	Proceedings of the ACM Conference on Computer and Communications Security
ISSN (Print)	1543-7221

Conference

Conference	28th ACM SIGSAC Conference on Computer and Communications Security, CCS 2022
Country/Territory	United States
City	Los Angeles
Period	7/11/22 → 11/11/22

Keywords

federated learning
model inconsistency
secure aggregation

Access to Document

10.1145/3548606.3560557

Cite this

Pasquini, D., Francati, D., & Ateniese, G. (2022). Eluding Secure Aggregation in Federated Learning via Model Inconsistency. In CCS 2022 - Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security (pp. 2429-2443). (Proceedings of the ACM Conference on Computer and Communications Security). Association for Computing Machinery (ACM). https://doi.org/10.1145/3548606.3560557

Pasquini, Dario ; Francati, Danilo ; Ateniese, Giuseppe. / Eluding Secure Aggregation in Federated Learning via Model Inconsistency. CCS 2022 - Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security. Association for Computing Machinery (ACM), 2022. pp. 2429-2443 (Proceedings of the ACM Conference on Computer and Communications Security).

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title = "Eluding Secure Aggregation in Federated Learning via Model Inconsistency",

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author = "Dario Pasquini and Danilo Francati and Giuseppe Ateniese",

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year = "2022",

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language = "English",

series = "Proceedings of the ACM Conference on Computer and Communications Security",

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Pasquini, D, Francati, D & Ateniese, G 2022, Eluding Secure Aggregation in Federated Learning via Model Inconsistency. in CCS 2022 - Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security. Proceedings of the ACM Conference on Computer and Communications Security, Association for Computing Machinery (ACM), pp. 2429-2443, 28th ACM SIGSAC Conference on Computer and Communications Security, CCS 2022, Los Angeles, United States, 7/11/22. https://doi.org/10.1145/3548606.3560557

Eluding Secure Aggregation in Federated Learning via Model Inconsistency. / Pasquini, Dario; Francati, Danilo; Ateniese, Giuseppe.
CCS 2022 - Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security. Association for Computing Machinery (ACM), 2022. p. 2429-2443 (Proceedings of the ACM Conference on Computer and Communications Security).

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

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T1 - Eluding Secure Aggregation in Federated Learning via Model Inconsistency

AU - Pasquini, Dario

AU - Francati, Danilo

AU - Ateniese, Giuseppe

PY - 2022/11/7

Y1 - 2022/11/7

KW - federated learning

KW - model inconsistency

KW - secure aggregation

UR - https://www.scopus.com/pages/publications/85143051304

U2 - 10.1145/3548606.3560557

DO - 10.1145/3548606.3560557

M3 - Conference contribution

AN - SCOPUS:85143051304

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

SP - 2429

EP - 2443

BT - CCS 2022 - Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security

PB - Association for Computing Machinery (ACM)

T2 - 28th ACM SIGSAC Conference on Computer and Communications Security, CCS 2022

Y2 - 7 November 2022 through 11 November 2022

ER -

Pasquini D, Francati D, Ateniese G. Eluding Secure Aggregation in Federated Learning via Model Inconsistency. In CCS 2022 - Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security. Association for Computing Machinery (ACM). 2022. p. 2429-2443. (Proceedings of the ACM Conference on Computer and Communications Security). doi: 10.1145/3548606.3560557

Eluding Secure Aggregation in Federated Learning via Model Inconsistency

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Eluding Secure Aggregation in Federated Learning via Model Inconsistency

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