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A Two-Stage Stochastic Programming Approach for the Key Management q-Composite Scheme

In: Handbook of Trustworthy Federated Learning

Author

Listed:
  • Maciej Rysz

    (Miami University)

  • Guanglin Xu

    (University of North Carolina at Charlotte)

  • Alexander Semenov

    (University of Florida)

Abstract

In federated learning, data is distributed across multiple devices or nodes, making secure and efficient information transfer a critical challenge. This requires the advancement of complex encryption strategies that can guarantee secure communications when one or more network sensors (nodes) are compromised (e.g., hacked), and when the network topology is not known a priori. In this article, we consider the q-Composite scheme, where a pair of nodes within proximity must share at least q keys to communicate. We introduce a stochastic optimization model for finding optimal key assignments that produce a desired level of communication security in settings where the network topology is unknown in advance. The model enables secure encryption strategies that are resilient against node capture, failures, and network topology changes. We present computational studies to demonstrate the efficacy of the proposed scheme.

Suggested Citation

  • Maciej Rysz & Guanglin Xu & Alexander Semenov, 2025. "A Two-Stage Stochastic Programming Approach for the Key Management q-Composite Scheme," Springer Optimization and Its Applications, in: My T. Thai & Hai N. Phan & Bhavani Thuraisingham (ed.), Handbook of Trustworthy Federated Learning, pages 197-219, Springer.
    • Handle: RePEc:spr:spochp:978-3-031-58923-2_7
    DOI: 10.1007/978-3-031-58923-2_7
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