Search for: All records

Data-dependent accesses to memory are necessary for many real-world applications, but their cost remains prohibitive in secure computation. Prior work either focused on minimizing the need for data-dependent access in these applications, or reduced its cost by improving oblivious RAM for secure computation (SC-ORAM). Despite extensive efforts to improve SC-ORAM, the most concretely efficient solutions still require ≈ 0.7 s per access to arrays of 230 entries. This plainly precludes using MPC in a number of settings. In this work, we take a pragmatic approach, exploring how concretely cheap MPC RAM access could be made if we are willing to allow one of the participants to learn the access pattern. We design a highly efficient Shared-Output Client-Server ORAM (SOCS-ORAM ) that has constant overhead, uses one round-trip of interaction per access, and whose access cost is independent of array size. SOCS-ORAM is useful in settings with hard performance constraints, where one party in the computation is more trust-worthy and is allowed to learn the RAM access pattern. Our SOCS-ORAM is assisted by a third helper party that helps initialize the protocol and is designed for the honest-majority semi-honest corruption model. We implement our construction in C++ and report its performance. For an array of length 230 with 4B entries, we communicate 13B per access and take essentially no overhead beyond network latency. 

Mobile Edge Computing (MEC) creates new infrastructure at the edges of the mobile networks, thus providing transformative opportunities for applications seeking latency benefits by operating closer to end-users and devices. However, the reduced network distance between the application endpoints of the MEC flows causes pattern shifts in the packet bursts exchanged at the network edges. The longer and denser bursts create a new source of contention that is not considered by current solutions. As a result, naively collocating applications onto the MEC tier can negatively affect latency-critical workloads, resulting in up to 73% packets experiencing as much as 3.8x increased latency. This makes it impossible to support latency-centric SLOs in MEC, obviating its expected benefits from MEC. This paper is the first to describe this new contention point in mobile networks and its potentially crippling impact on the achievable latency benefit from MEC. We propose ShapeShifter, a new component in the MEC architecture which solves the MEC latency contention problem through adaptive latency-centric burst management of MEC flows. ShapeShifter is effective - it eliminates SLO violations for latency-critical applications and improves application performance in multi-tenant scenarios by up to 3.8 x – and practical – it can be deployed with minimal disruption to the current mobile network ecosystem.