TY - GEN
T1 - Algebraic distinguishers
T2 - 18th International Conference on Theory of Cryptography, TCCC 2020
AU - Rotem, Lior
AU - Segev, Gil
N1 - Publisher Copyright: © International Association for Cryptologic Research 2020.
PY - 2020
Y1 - 2020
N2 - The algebraic group model, introduced by Fuchsbauer, Kiltz and Loss (CRYPTO ’18), is a substantial relaxation of the generic group model capturing algorithms that may exploit the representation of the underlying group. This idealized yet realistic model was shown useful for reasoning about cryptographic assumptions and security properties defined via computational problems. However, it does not generally capture assumptions and properties defined via decisional problems. As such problems play a key role in the foundations and applications of cryptography, this leaves a significant gap between the restrictive generic group model and the standard model. We put forward the notion of algebraic distinguishers, strengthening the algebraic group model by enabling it to capture decisional problems. Within our framework we then reveal new insights on the algebraic interplay between a wide variety of decisional assumptions. These include the decisional Diffie-Hellman assumption, the family of Linear assumptions in multilinear groups, and the family of Uber assumptions in bilinear groups. Our main technical results establish that, from an algebraic perspective, these decisional assumptions are in fact all polynomially equivalent to either the most basic discrete logarithm assumption or to its higher-order variant, the q-discrete logarithm assumption. On the one hand, these results increase the confidence in these strong decisional assumptions, while on the other hand, they enable to direct cryptanalytic efforts towards either extracting discrete logarithms or significantly deviating from standard algebraic techniques.
AB - The algebraic group model, introduced by Fuchsbauer, Kiltz and Loss (CRYPTO ’18), is a substantial relaxation of the generic group model capturing algorithms that may exploit the representation of the underlying group. This idealized yet realistic model was shown useful for reasoning about cryptographic assumptions and security properties defined via computational problems. However, it does not generally capture assumptions and properties defined via decisional problems. As such problems play a key role in the foundations and applications of cryptography, this leaves a significant gap between the restrictive generic group model and the standard model. We put forward the notion of algebraic distinguishers, strengthening the algebraic group model by enabling it to capture decisional problems. Within our framework we then reveal new insights on the algebraic interplay between a wide variety of decisional assumptions. These include the decisional Diffie-Hellman assumption, the family of Linear assumptions in multilinear groups, and the family of Uber assumptions in bilinear groups. Our main technical results establish that, from an algebraic perspective, these decisional assumptions are in fact all polynomially equivalent to either the most basic discrete logarithm assumption or to its higher-order variant, the q-discrete logarithm assumption. On the one hand, these results increase the confidence in these strong decisional assumptions, while on the other hand, they enable to direct cryptanalytic efforts towards either extracting discrete logarithms or significantly deviating from standard algebraic techniques.
UR - http://www.scopus.com/inward/record.url?scp=85098266018&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-64381-2_13
DO - 10.1007/978-3-030-64381-2_13
M3 - منشور من مؤتمر
SN - 9783030643805
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 366
EP - 389
BT - Theory of Cryptography - 18th International Conference, TCC 2020, Proceedings
A2 - Pass, Rafael
A2 - Pietrzak, Krzysztof
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 16 November 2020 through 19 November 2020
ER -