Star-Specific Key-Homomorphic PRFs From Learning With Linear Regression
Star-Specific Key-Homomorphic PRFs From Learning With Linear Regression
We introduce a novel method to derandomize the learning with errors (LWE) problem by generating deterministic yet sufficiently independent LWE instances that are constructed by using linear regression models, which are generated via (wireless) communication errors. We also introduce star-specific key-homomorphic (SSKH) pseudorandom functions (PRFs), which are defined by the …