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Choosing Parameters for the Subfield Lattice Attack Against Overstretched NTRU

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posted on 2024-11-15, 08:42 authored by Steven DuongSteven Duong, Masaya Yasuda, Tsuyoshi Takagi
Albrecht et al. [1] at Crypto 2016 and Cheon et al. [4] at ANTS 2016 independently presented a subfield attack on overstretched NTRU problem. Their idea is to map the public key down to the subfield (by norm and trace map respectively) and hence obtain a lattice of smaller dimension for which a lattice reduction algorithm is efficiently applicable. At Eurocrypt 2017, Kirchner and Fouque proposed another variant attack which exploits the presence of orthogonal bases within the cyclotomic number rings and instead of using the matrix of the public key in the subfield, they use the multiplication matrix by the public key in the full field and apply a lattice reduction algorithm to a suitable projected lattice of smaller dimension. They also showed a tight estimation of the parameters broken by lattice reduction and implementation results that their attack is better than the subfield attack. In this paper, we exploit technical results from Kirchner and Fouque [12] for the relative norm of field elements in the subfield and we use Hermite factor for estimating the output of a lattice basis reduction algorithm in order to analyze general choice of parameters for the subfield attack by Albrecht et al. [1]. As a result, we obtain the estimation for better choices of the subfields for which the attack works with smaller modulus. Our experiment results show that we can attack overstretched NTRU with modulus smaller than that of Albrecht et al. and of Kirchner and Fouque.

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Citation

Duong, D. Hoang., Yasuda, M. & Takagi, T. (2017). Choosing Parameters for the Subfield Lattice Attack Against Overstretched NTRU. Lecture Notes in Computer Science, 10599 79-91. Information Security 20th International Conference, ISC 2017, Ho Chi Minh City, Vietnam, November 22-24, 2017, Proceedings

Journal title

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume

10599 LNCS

Pagination

79-91

Language

English

RIS ID

131089

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