Raghavendra Kulkarni1, Venkata Satya Suresh kumar Kondeti1, Binu Sudhakaran Pillai2, Surendran Rajendran3,*
CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-23, 2026, DOI:10.32604/cmc.2025.069835
- 10 November 2025
Abstract The next-generation RAN, known as Open Radio Access Network (ORAN), allows for several advantages, including cost-effectiveness, network flexibility, and interoperability. Now ORAN applications, utilising machine learning (ML) and artificial intelligence (AI) techniques, have become standard practice. The need for Federated Learning (FL) for ML model training in ORAN environments is heightened by the modularised structure of the ORAN architecture and the shortcomings of conventional ML techniques. However, the traditional plaintext model update sharing of FL in multi-BS contexts is susceptible to privacy violations such as deep-leakage gradient assaults and inference. Therefore, this research presents a… More >
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