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Author

Dong-Joon Shin

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Preprint Jul 2026

Information-Theoretically Secure Aggregation for Lightweight Federated Learning: Resilient to Dropouts and Adversaries

This work proposes a lightweight and information-theoretically secure aggregation framework that securely computes the majority vote (MV) polynomial through single-round secure multiplication, ensuring end-to-end information-theoretic security under the honest-majority assumption while revealing only the final aggregat...

Hyeong-Gun Joo, Songnam Hong, Dong-Joon Shin · 0 citations
#machine learning Jul 2026

Information-Theoretically Secure Aggregation for Lightweight Federated Learning: Resilient to Dropouts and Adversaries

This work proposes a lightweight and information-theoretically secure aggregation framework that securely computes the majority vote (MV) polynomial through single-round secure multiplication, ensuring end-to-end information-theoretic security under the honest-majority assumption while revealing only the final aggregat...

Hyeong-Gun Joo, Songnam Hong, Dong-Joon Shin · 0 citations

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