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Salsa Fresca: Angular Embeddings and Pre-Training for ML Attacks on Learning With Errors
Our architecture improvements enable scaling to larger-dimension LWE problems: this work is the first instance of ML attacks recovering sparse binary secrets in dimension $n=1024$, the smallest dimension used in practice for homomorphic encryption applications of LWE where sparse binary secrets are proposed.
SALSA PICANTE: a machine learning attack on LWE with binary secrets
However, this attack assumes access to millions of eavesdropped LWE samples and fails at higher Hamming weights or dimensions.
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