Implementing joux-vitse’s crossbred algorithm for solving MQ Systems over F\u3csub\u3e2\u3c/sub\u3eon GPUs

Abstract

\u3cp\u3eThe hardness of solving multivariate quadratic (MQ) systems is the underlying problem for multivariate-based schemes in the field of post-quantum cryptography. The concrete, practical hardness of this problem needs to be measured by state-of-the-art algorithms and high-performance implementations. We describe, implement, and evaluate an adaption of the Crossbred algorithm by Joux and Vitse from 2017 for solving MQ systems over F\u3csub\u3e2\u3c/sub\u3e. Our adapted algorithm is highly parallelizable and is suitable for solving MQ systems on GPU architectures. Our implementation is able to solve an MQ system of 134 equations in 67 variables in 98.39 hours using one single commercial Nvidia GTX 980 graphics card, while the original Joux-Vitse algorithm requires 6200 CPU-hours for the same problem size. We used our implementation to solve all the Fukuoka Type-I MQ challenges for n ∈ {55,…74}. Based on our implementation, we estimate that the expected computation time for solving an MQ system of 80 equations in 84 variables is about one year using a cluster of 3600 GTX 980 graphics cards. These parameters have been proposed for 80-bit security by, e.g., Sakumoto, Shirai, and Hiwatari at Crypto 2011.\u3c/p\u3