KyFrog: A High-Security LWE-Based KEM Inspired by ML-KEM
By: Victor Duarte Melo, Willian J. Buchanan
Potential Business Impact:
Makes secret messages super hard to steal.
KyFrog is a conservative Learning-with-Errors (LWE) key-encapsulation mechanism designed to explore an alternative operating point compared to schemes with relatively small public keys and ciphertexts. KyFrog uses a larger dimension ($n = 1024$) and a small prime modulus $q = 1103$, together with narrow error distributions with standard deviations $σ_s = σ_e = 1.4$, to target approximately $2^{325}$ classical and quantum security against state-of-the-art lattice attacks under standard cost models, as estimated using the Lattice Estimator. The price paid for this security margin is an extremely large KEM ciphertext (about 0.5 MiB), while public and secret keys remain in the same ballpark as ML-KEM. We describe the design rationale, parameter search methodology, and implementation details of KyFrog, and we compare its asymptotic security and concrete parameter sizes with the ML-KEM standard. All code and data for this work are released as free and open-source software, with the full C++23 implementation and experimental scripts available at: https://github.com/victormeloasm/kyfrog
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