In this letter, we delve into a scenario where a user aims to compute
polynomial functions using their own data as well as data obtained from
distributed sources. To accomplish this, the user enlists the assistance of N
distributed workers, thereby defining a problem we refer to as
privacy-preserving polynomial computing over distributed data. To address this
challenge, we propose an approach founded upon Lagrange encoding. Our method
not only possesses the ability to withstand the presence of stragglers and
byzantine workers but also ensures the preservation of security. Specifically,
even if a coalition of X workers collude, they are unable to acquire any
knowledge pertaining to the data originating from the distributed sources or
the user