  We investigate the problem of privacy preserving distributed matrix
multiplication in edge networks using multi-party computation (MPC). Coded
multi-party computation (CMPC) is an emerging approach to reduce the required
number of workers in MPC by employing coded computation. Existing CMPC
approaches usually combine coded computation algorithms designed for efficient
matrix multiplication with MPC. We show that this approach is not efficient. We
design a novel CMPC algorithm; PolyDot coded MPC (PolyDot-CMPC) by using a
recently proposed coded computation algorithm; PolyDot codes. We exploit
"garbage terms" that naturally arise when polynomials are constructed in the
design of PolyDot-CMPC to reduce the number of workers needed for
privacy-preserving computation. We show that entangled polynomial codes, which
are consistently better than PolyDot codes in coded computation setup, are not
necessarily better than PolyDot-CMPC in MPC setting.
