Private and Secure Coded Computation in Straggler-Exploiting Distributed Matrix Multiplication

In this paper, we consider coded computation for matrix multiplication tasks in distributed computing, which can mitigate the effect of slow workers, called stragglers, by a coding approach. We assume that the stragglers' computation results can be leveraged at the master by assigning multiple sub-tasks to the workers. In this scenario, we propose a new coded computation scheme to preserve the data privacy and security from the non-colluding workers. We also prove that the data privacy and security constraints are satisfied in our scheme in an information-theoretic sense.