Secure Multiparty Computation - SMC is one of two main methods for building Privacy - Preserving Data Mining - PPDM. Among SMC techniques, Secure Sum Protocol - SSP is the most basic one. For SMC solutions in general and SSPs in particular, the problem of optimizing three parameters: accuracy, performance, and privacy still poses many challenges for researchers. However, most of the SSP solutions proposed in the past have poor performance or can not preserve privacy. In this paper, I present a new SSP solution that more effectively balances the two above parameters. Besides, in this paper, I build a general mathematical constraint model between performance and privacy.