FicGCN proposes sparse intra-ciphertext aggregation and node reordering to reduce rotation overhead in homomorphically encrypted GCN inference, achieving up to 4.10x speedup over state-of-the-art.
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FicGCN: Unveiling the Homomorphic Encryption Efficiency from Irregular Graph Convolutional Networks
FicGCN proposes sparse intra-ciphertext aggregation and node reordering to reduce rotation overhead in homomorphically encrypted GCN inference, achieving up to 4.10x speedup over state-of-the-art.