International Association
for Cryptologic Research

This paper introduces DAWN, a compact and efficient NTRU encryption utilizing double encoding, which is provably secure under the NTRU assumption and the Ring-LWE assumption. We propose a novel technique for NTRU encryption called the zero divisor encoding. Unlike the polynomial encoding technique proposed by Hoffstein and Silverman (2001) and the vector encoding technique proposed by Zhang, Feng, and Yan in NEV (Asiacrypt 2023), our zero divisor encoding technique leverages the algebraic structure of the ring used in NTRU, enabling greater ciphertext compression while maintaining negligible decryption failure. We further develop a paradigm for NTRU encryption called the double encoding paradigm to maximize the potential of the zero divisor encoding. This paradigm transforms optimizing an NTRU-based encryption into constructing a better encoding within the NTRU context, providing more concrete direction for scheme development. Several previous NTRU encryptions can be situated within this paradigm with different parameters, facilitating direct comparison. We instantiate this paradigm based on the provably IND-CPA secure NTRU variant by Stehlé and Steinfeld (Eurocrypt 2011) to achieve an IND-CPA secure PKE, and subsequently employ the Fujisaki-Okamoto transformation to achieve an IND-CCA secure KEM. We present two parameter settings of DAWN: DAWN-alpha minimizes ciphertext size, achieving lengths of 436 bytes under NIST-I security and 973 bytes under NIST-V security; DAWN-beta minimizes the combined size of the public key and ciphertext, attaining combined sizes of 964 bytes under NIST-I security and 2054 bytes under NIST-V security. DAWN achieves superior compactness and performance among current lattice-based KEMs without introducing additional security assumptions. Compared to NEV (Asiacrypt 2023), the previously leading NTRU-based KEM in balancing compactness and performance, DAWN demonstrates 20%-29% greater compactness at approximate security levels and decryption failure probabilities, while executing 1.1X-2.0X faster in a complete ephemeral key exchange process.

This paper presents a novel approach to optimizing the linear layer of block ciphers using the matrix decomposition framework. It is observed that the reduction properties proposed by Xiang et al. (in FSE 2020) need to be improved. To address these limitations, we propose a new reduction framework with a complete reduction algorithm and swapping algorithm. Our approach formulates matrix decomposition as a new framework with an adaptive objective function and converts the problem to a Graph Isomorphism problem (GI problem). Using the new reduction algorithm, we were able to achieve lower XOR counts and depths of quantum implementations under the s-XOR metric. Our results outperform previous works for many linear layers of block ciphers and hash functions; some of them are better than the current g-XOR implementation. For the AES MixColumn operation, we get two implementations with 91 XOR counts and depth 13 of in-place quantum implementation, respectively.