A Non-Disclosure Incentive Mechanism for Federated Learning Via Alternating-offers Bargaining 


Vol. 50,  No. 9, pp. 1343-1352, Sep.  2025
10.7840/kics.2025.50.9.1343


PDF Full-Text
  Abstract

In this paper, we propose a non-disclosure incentive mechanism for federated learning via alternating-offers bargaining which does not utilize device information of clients while improving learning performance and approximating an optimal resource allocation. By defining utility functions of clients that reflect their self estimated performances and determining minimum compensation information, clients can be selected for participation without revealing their device information such as loss of their local model or dataset size. To determine the compensation resource allocation, server and clients perform alternating-offers bargaining, which does not require sharing their utility functions. Experiment results show that the proposed incentive mechanism can speed up convergence, improve test accuracy, and induce compensation resource allocation near the Nash bargaining soution while not revealing the device information of clients.

  Statistics
Cumulative Counts from November, 2022
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


  Related Articles
  Cite this article

[IEEE Style]

S. Jin, C. Cha, H. Park, "A Non-Disclosure Incentive Mechanism for Federated Learning Via Alternating-offers Bargaining," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 9, pp. 1343-1352, 2025. DOI: 10.7840/kics.2025.50.9.1343.

[ACM Style]

Suyeon Jin, Chaeyeon Cha, and Hyunggon Park. 2025. A Non-Disclosure Incentive Mechanism for Federated Learning Via Alternating-offers Bargaining. The Journal of Korean Institute of Communications and Information Sciences, 50, 9, (2025), 1343-1352. DOI: 10.7840/kics.2025.50.9.1343.

[KICS Style]

Suyeon Jin, Chaeyeon Cha, Hyunggon Park, "A Non-Disclosure Incentive Mechanism for Federated Learning Via Alternating-offers Bargaining," The Journal of Korean Institute of Communications and Information Sciences, vol. 50, no. 9, pp. 1343-1352, 9. 2025. (https://doi.org/10.7840/kics.2025.50.9.1343)
Vol. 50, No. 9 Index

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)






pISSN : 1226 - 4717
eISSN : 2287 - 3880