Standing Firm in 5G: A Single-Round, Dropout-Resilient Secure Aggregation for Federated Learning
Fuente:
arXiv
Salvato in:
| Autori principali: | , , , , |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866913832214986752 |
|---|---|
| author | Zhang, Yiwei Behnia, Rouzbeh Karim, Imtiaz Yavuz, Attila A. Bertino, Elisa |
| author_facet | Zhang, Yiwei Behnia, Rouzbeh Karim, Imtiaz Yavuz, Attila A. Bertino, Elisa |
| contents | Federated learning (FL) is well-suited to 5G networks, where many mobile devices generate sensitive edge data. Secure aggregation protocols enhance privacy in FL by ensuring that individual user updates reveal no information about the underlying client data. However, the dynamic and large-scale nature of 5G-marked by high mobility and frequent dropouts-poses significant challenges to the effective adoption of these protocols. Existing protocols often require multi-round communication or rely on fixed infrastructure, limiting their practicality. We propose a lightweight, single-round secure aggregation protocol designed for 5G environments. By leveraging base stations for assisted computation and incorporating precomputation, key-homomorphic pseudorandom functions, and t-out-of-k secret sharing, our protocol ensures efficiency, robustness, and privacy. Experiments show strong security guarantees and significant gains in communication and computation efficiency, making the approach well-suited for real-world 5G FL deployments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_07148 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Standing Firm in 5G: A Single-Round, Dropout-Resilient Secure Aggregation for Federated Learning Zhang, Yiwei Behnia, Rouzbeh Karim, Imtiaz Yavuz, Attila A. Bertino, Elisa Cryptography and Security Networking and Internet Architecture Federated learning (FL) is well-suited to 5G networks, where many mobile devices generate sensitive edge data. Secure aggregation protocols enhance privacy in FL by ensuring that individual user updates reveal no information about the underlying client data. However, the dynamic and large-scale nature of 5G-marked by high mobility and frequent dropouts-poses significant challenges to the effective adoption of these protocols. Existing protocols often require multi-round communication or rely on fixed infrastructure, limiting their practicality. We propose a lightweight, single-round secure aggregation protocol designed for 5G environments. By leveraging base stations for assisted computation and incorporating precomputation, key-homomorphic pseudorandom functions, and t-out-of-k secret sharing, our protocol ensures efficiency, robustness, and privacy. Experiments show strong security guarantees and significant gains in communication and computation efficiency, making the approach well-suited for real-world 5G FL deployments. |
| title | Standing Firm in 5G: A Single-Round, Dropout-Resilient Secure Aggregation for Federated Learning |
| topic | Cryptography and Security Networking and Internet Architecture |
| url | https://arxiv.org/abs/2505.07148 |