Author

Yiting Tan

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Open access 2026

SURGE: Sparse Updates With Randomized Guarding and Selective Encryption for Secure Federated Learning

SURGE targets empirical attack resistance under the honest-but-curious server model, rather than a formal privacy guarantee, and drives membership inference performance close to random guessing and substantially degrades the quality of gradient inversion reconstructions.

Xuanchi Li, Yiting Tan, Jing Wen et al. · IEEE Access · 0 citations