TY - GEN
T1 - Generating a random string with a fixed weight
AU - Drucker, Nir
AU - Gueron, Shay
N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - Generating, uniformly at random, a binary or a ternary string with a fixed length L and a prescribed weight W, is a step in several quantum safe cryptosystems (e. g., BIKE, NTRUEncrypt, NTRU LPrime, Lizard, McEliece). This fixed weight vector selection generation is often implemented via a shuffling method or a rejection method, but not always in “constant time” side channel protected flow. A recently suggested constant time algorithm for this problem, uses Network Sorting and turns out to be quite efficient. This paper proposes a new method for this computation, with a side channel protected implementation. We compare it to the other methods for different combinations of L and W values. Our method turns out to be the fastest approach for the cases where L is (relatively) short and (formula presented). For example, this range falls within the parameters of NTRU LPrime, where our method achieves a 3× speedup in the string generation. This leads to an overall 1.14× speedup for the NTRU LPrime key generation.
AB - Generating, uniformly at random, a binary or a ternary string with a fixed length L and a prescribed weight W, is a step in several quantum safe cryptosystems (e. g., BIKE, NTRUEncrypt, NTRU LPrime, Lizard, McEliece). This fixed weight vector selection generation is often implemented via a shuffling method or a rejection method, but not always in “constant time” side channel protected flow. A recently suggested constant time algorithm for this problem, uses Network Sorting and turns out to be quite efficient. This paper proposes a new method for this computation, with a side channel protected implementation. We compare it to the other methods for different combinations of L and W values. Our method turns out to be the fastest approach for the cases where L is (relatively) short and (formula presented). For example, this range falls within the parameters of NTRU LPrime, where our method achieves a 3× speedup in the string generation. This leads to an overall 1.14× speedup for the NTRU LPrime key generation.
KW - Coding
KW - Combinatorics
KW - Post Quantum Cryptography
KW - Software optimization
UR - http://www.scopus.com/inward/record.url?scp=85068235168&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/978-3-030-20951-3_13
DO - https://doi.org/10.1007/978-3-030-20951-3_13
M3 - Conference contribution
SN - 9783030209506
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 141
EP - 155
BT - Cyber Security Cryptography and Machine Learning - 3rd International Symposium, CSCML 2019, Proceedings
A2 - Dolev, Shlomi
A2 - Hendler, Danny
A2 - Lodha, Sachin
A2 - Yung, Moti
PB - Springer Verlag
T2 - 3rd International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2019
Y2 - 27 June 2019 through 28 June 2019
ER -