|| Private and Secure Coded Computation in Straggler-Exploiting Distributed Matrix Multiplication
||Heecheol Yang, Chungnam National University, Korea (South); Sangwoo Hong, Jungwoo Lee, Seoul National University, Korea (South)|
||D5-S3-T1: Secure Distributed Computation
||Friday, 16 July, 22:40 - 23:00
||Friday, 16 July, 23:00 - 23:20
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.