Verifiable Fairness: Privacy–preserving Computation of Fairness for Machine Learning Systems

Ehsan Toreini; Maryam Mehrnezhad; Aad van Moorsel

doi:10.1007/978-3-031-54129-2_34

Verifiable Fairness: Privacy–preserving Computation of Fairness for Machine Learning Systems

Ehsan Toreini, Maryam Mehrnezhad, Aad van Moorsel

Department of Information Security

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

Original language	English
Title of host publication	Computer Security. ESORICS 2023 International Workshops
Subtitle of host publication	CPS4CIP, ADIoT, SecAssure, WASP, TAURIN, PriST-AI, and SECAI, The Hague, The Netherlands, September 25–29, 2023, Revised Selected Papers, Part II
Editors	Sokratis Katsikas, Habtamu Abie, Silvio Ranise, Luca Verderame, Enrico Cambiaso, Rita Ugarelli, Isabel Praça, Wenjuan Li, Weizhi Meng, Steven Furnell, Basel Katt, Sandeep Pirbhulal, Ankur Shukla, Michele Ianni, Mila Dalla Preda, Kim-Kwang Raymond Choo, Miguel Pupo Correia, Abhishta Abhishta, Giovanni Sileno, Mina Alishahi, Harsha Kalutarage, Naoto Yanai
Publisher	Springer, [Cham]
Pages	569-584
Number of pages	16
ISBN (Print)	9783031541285
DOIs	https://doi.org/10.1007/978-3-031-54129-2_34
Publication status	Published - 12 Mar 2024
Event	International Workshops which were held in conjunction with 28th European Symposium on Research in Computer Security, ESORICS 2023 - The Hague, Netherlands Duration: 25 Sept 2023 → 29 Sept 2023

Publication series

Name	Lecture Notes in Computer Science
Volume	14399 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Workshops which were held in conjunction with 28th European Symposium on Research in Computer Security, ESORICS 2023
Country/Territory	Netherlands
City	The Hague
Period	25/09/23 → 29/09/23

Keywords

artificial intelligence
fairness computation
machine learning fairness
trustworthiness

Access to Document

10.1007/978-3-031-54129-2_34

Cite this

Toreini, E., Mehrnezhad, M., & van Moorsel, A. (2024). Verifiable Fairness: Privacy–preserving Computation of Fairness for Machine Learning Systems. In S. Katsikas, H. Abie, S. Ranise, L. Verderame, E. Cambiaso, R. Ugarelli, I. Praça, W. Li, W. Meng, S. Furnell, B. Katt, S. Pirbhulal, A. Shukla, M. Ianni, M. Dalla Preda, K.-K. R. Choo, M. Pupo Correia, A. Abhishta, G. Sileno, M. Alishahi, H. Kalutarage, ... N. Yanai (Eds.), Computer Security. ESORICS 2023 International Workshops: CPS4CIP, ADIoT, SecAssure, WASP, TAURIN, PriST-AI, and SECAI, The Hague, The Netherlands, September 25–29, 2023, Revised Selected Papers, Part II (pp. 569-584). (Lecture Notes in Computer Science ; Vol. 14399 LNCS). Springer, [Cham]. https://doi.org/10.1007/978-3-031-54129-2_34

Toreini, Ehsan ; Mehrnezhad, Maryam ; van Moorsel, Aad. / Verifiable Fairness : Privacy–preserving Computation of Fairness for Machine Learning Systems. Computer Security. ESORICS 2023 International Workshops: CPS4CIP, ADIoT, SecAssure, WASP, TAURIN, PriST-AI, and SECAI, The Hague, The Netherlands, September 25–29, 2023, Revised Selected Papers, Part II. editor / Sokratis Katsikas ; Habtamu Abie ; Silvio Ranise ; Luca Verderame ; Enrico Cambiaso ; Rita Ugarelli ; Isabel Praça ; Wenjuan Li ; Weizhi Meng ; Steven Furnell ; Basel Katt ; Sandeep Pirbhulal ; Ankur Shukla ; Michele Ianni ; Mila Dalla Preda ; Kim-Kwang Raymond Choo ; Miguel Pupo Correia ; Abhishta Abhishta ; Giovanni Sileno ; Mina Alishahi ; Harsha Kalutarage ; Naoto Yanai. Springer, [Cham], 2024. pp. 569-584 (Lecture Notes in Computer Science ).

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Toreini, E, Mehrnezhad, M & van Moorsel, A 2024, Verifiable Fairness: Privacy–preserving Computation of Fairness for Machine Learning Systems. in S Katsikas, H Abie, S Ranise, L Verderame, E Cambiaso, R Ugarelli, I Praça, W Li, W Meng, S Furnell, B Katt, S Pirbhulal, A Shukla, M Ianni, M Dalla Preda, K-KR Choo, M Pupo Correia, A Abhishta, G Sileno, M Alishahi, H Kalutarage & N Yanai (eds), Computer Security. ESORICS 2023 International Workshops: CPS4CIP, ADIoT, SecAssure, WASP, TAURIN, PriST-AI, and SECAI, The Hague, The Netherlands, September 25–29, 2023, Revised Selected Papers, Part II. Lecture Notes in Computer Science , vol. 14399 LNCS, Springer, [Cham], pp. 569-584, International Workshops which were held in conjunction with 28th European Symposium on Research in Computer Security, ESORICS 2023, The Hague, Netherlands, 25/09/23. https://doi.org/10.1007/978-3-031-54129-2_34

Verifiable Fairness: Privacy–preserving Computation of Fairness for Machine Learning Systems. / Toreini, Ehsan; Mehrnezhad, Maryam; van Moorsel, Aad.
Computer Security. ESORICS 2023 International Workshops: CPS4CIP, ADIoT, SecAssure, WASP, TAURIN, PriST-AI, and SECAI, The Hague, The Netherlands, September 25–29, 2023, Revised Selected Papers, Part II. ed. / Sokratis Katsikas; Habtamu Abie; Silvio Ranise; Luca Verderame; Enrico Cambiaso; Rita Ugarelli; Isabel Praça; Wenjuan Li; Weizhi Meng; Steven Furnell; Basel Katt; Sandeep Pirbhulal; Ankur Shukla; Michele Ianni; Mila Dalla Preda; Kim-Kwang Raymond Choo; Miguel Pupo Correia; Abhishta Abhishta; Giovanni Sileno; Mina Alishahi; Harsha Kalutarage; Naoto Yanai. Springer, [Cham], 2024. p. 569-584 (Lecture Notes in Computer Science ; Vol. 14399 LNCS).

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

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T1 - Verifiable Fairness

T2 - International Workshops which were held in conjunction with 28th European Symposium on Research in Computer Security, ESORICS 2023

AU - Toreini, Ehsan

AU - Mehrnezhad, Maryam

AU - van Moorsel, Aad

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

PY - 2024/3/12

Y1 - 2024/3/12

KW - artificial intelligence

KW - fairness computation

KW - machine learning fairness

KW - trustworthiness

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DO - 10.1007/978-3-031-54129-2_34

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AN - SCOPUS:85188712316

SN - 9783031541285

T3 - Lecture Notes in Computer Science

SP - 569

EP - 584

BT - Computer Security. ESORICS 2023 International Workshops

A2 - Katsikas, Sokratis

A2 - Abie, Habtamu

A2 - Ranise, Silvio

A2 - Verderame, Luca

A2 - Cambiaso, Enrico

A2 - Ugarelli, Rita

A2 - Praça, Isabel

A2 - Li, Wenjuan

A2 - Meng, Weizhi

A2 - Furnell, Steven

A2 - Katt, Basel

A2 - Pirbhulal, Sandeep

A2 - Shukla, Ankur

A2 - Ianni, Michele

A2 - Dalla Preda, Mila

A2 - Choo, Kim-Kwang Raymond

A2 - Pupo Correia, Miguel

A2 - Abhishta, Abhishta

A2 - Sileno, Giovanni

A2 - Alishahi, Mina

A2 - Kalutarage, Harsha

A2 - Yanai, Naoto

PB - Springer, [Cham]

Y2 - 25 September 2023 through 29 September 2023

ER -

Toreini E, Mehrnezhad M, van Moorsel A. Verifiable Fairness: Privacy–preserving Computation of Fairness for Machine Learning Systems. In Katsikas S, Abie H, Ranise S, Verderame L, Cambiaso E, Ugarelli R, Praça I, Li W, Meng W, Furnell S, Katt B, Pirbhulal S, Shukla A, Ianni M, Dalla Preda M, Choo KKR, Pupo Correia M, Abhishta A, Sileno G, Alishahi M, Kalutarage H, Yanai N, editors, Computer Security. ESORICS 2023 International Workshops: CPS4CIP, ADIoT, SecAssure, WASP, TAURIN, PriST-AI, and SECAI, The Hague, The Netherlands, September 25–29, 2023, Revised Selected Papers, Part II. Springer, [Cham]. 2024. p. 569-584. (Lecture Notes in Computer Science ). doi: 10.1007/978-3-031-54129-2_34

Verifiable Fairness: Privacy–preserving Computation of Fairness for Machine Learning Systems

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