AI Gauges Cryptanalysis Effort on Public-Key Algorithms

Researchers used AI models to estimate the amount of cryptanalysis effort spent on various public-key algorithms by analyzing published academic papers. The study focused on ECDLP, structured and plain lattices, syndrome decoding, and their comparators, converting papers into estimated research-allocation years. Lattices have recently surpassed elliptic curves in cumulative analysis under stated productivity assumptions. The findings are based on published work, so they exclude unpublished academic research and secret intelligence cryptanalysis.