Machine learning for modular multiplication
CoRR(2024)
摘要
Motivated by cryptographic applications, we investigate two machine learning
approaches to modular multiplication: namely circular regression and a
sequence-to-sequence transformer model. The limited success of both methods
demonstrated in our results gives evidence for the hardness of tasks involving
modular multiplication upon which cryptosystems are based.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要