Secure Coded Distributed Computing
Shanuja Sasi, Onur Günlü
TL;DR
The paper tackles information-theoretic security in coded distributed computing within the MapReduce framework by addressing secure data shuffling and secure coded computing. It constructs PDA-based schemes combined with secret sharing to achieve ITS guarantees, deriving explicit tradeoffs between computation load $r$ and communication load $L$ in terms PDA parameters $(K,F,Z,S)$. The main results show secure data shuffling with $r=Z/F$ and $L= rac{S}{KF}+ \sum_{g=2}^{K}\frac{S_g}{KF(g-1)}$, and secure coded computing with $r=\frac{Z}{F-Z}$ and $L=\frac{S}{K(F-Z)}+ \sum_{g=2}^{K}\frac{S_g}{K(F-Z)(g-1)}$, including an illustrative PDA example and overheads from secret-key storage. These contributions provide concrete, information-theoretic security guarantees and practical load tradeoffs for low-latency secure data processing in edge-enabled DC systems.
Abstract
In this paper, we consider two critical aspects of security in the distributed computing (DC) model: secure data shuffling and secure coded computing. It is imperative that any external entity overhearing the transmissions does not gain any information about the intermediate values (IVs) exchanged during the shuffling phase of the DC model. Our approach ensures IV confidentiality during data shuffling. Moreover, each node in the system must be able to recover the IVs necessary for computing its output functions but must also remain oblivious to the IVs associated with output functions not assigned to it. We design secure DC methods and establish achievable limits on the tradeoffs between the communication and computation loads to contribute to the advancement of secure data processing in distributed systems.