Multiplicative Learning with Errors and Cryptosystems
Chunsheng Gu
Abstract
Abstract: We introduce a new concept, called multiplicative learning with errors (MLWE), which is a corresponding multiplicative version of the additive learning with errors (LWE), and show the equivalence between the decisional version and the search version for MLWE such that p is a product of sufficiently large smoothing prime factors. Then we construct the MLWE-based private-key and public-key encryption schemes, whose securities are based on the worst-case hardness assumption of the MLWE problem. Finally, we discuss how to extend the LWE on additive group to the LWE on general abelian group.