Anrin Chakraborti (Stony Brook University), Radu Sion (Stony Brook University)

ConcurORAM is a parallel, multi-client oblivious RAM (ORAM) that eliminates waiting for concurrent stateless clients and allows over-all throughput to scale gracefully, without requiring trusted third party components (proxies) or direct inter-client coordination. A key insight behind ConcurORAM is the fact that, during multi-client data access, only a subset of the concurrently-accessed server-hosted data structures require access privacy guarantees. Everything else can be safely implemented as oblivious data structures that are later synced securely and efficiently during an ORAM “eviction”.

Further, since a major contributor to latency is the eviction– in which client-resident data is reshuffled and reinserted back encrypted into the main server database – ConcurORAM also enables multiple concurrent clients to evict asynchronously, in parallel (without compromising consistency), and in the back-ground without having to block ongoing queries. As a result, throughput scales well with increasing number of concurrent clients and is not significantly impacted by evictions. For example, about 65 queries per second can be executed in parallel by 30 concurrent clients, a 2x speedup over the state-of-the-art. The query access time for individual clients increases by only 2x when compared to a single-client deployment.

View More Papers

Sereum: Protecting Existing Smart Contracts Against Re-Entrancy Attacks

Michael Rodler (University of Duisburg-Essen), Wenting Li (NEC Laboratories, Germany), Ghassan O. Karame (NEC Laboratories, Germany), Lucas Davi (University of Duisburg-Essen)

Read More

Data Oblivious ISA Extensions for Side Channel-Resistant and High...

Jiyong Yu (UIUC), Lucas Hsiung (UIUC), Mohamad El'Hajj (UIUC), Christopher W. Fletcher (UIUC)

Read More

ML-Leaks: Model and Data Independent Membership Inference Attacks and...

Ahmed Salem (CISPA Helmholtz Center for Information Security), Yang Zhang (CISPA Helmholtz Center for Information Security), Mathias Humbert (Swiss Data Science Center, ETH Zurich/EPFL), Pascal Berrang (CISPA Helmholtz Center for Information Security), Mario Fritz (CISPA Helmholtz Center for Information Security), Michael Backes (CISPA Helmholtz Center for Information Security)

Read More

Profit: Detecting and Quantifying Side Channels in Networked Applications

Nicolás Rosner (University of California, Santa Barbara), Ismet Burak Kadron (University of California, Santa Barbara), Lucas Bang (Harvey Mudd College), Tevfik Bultan (University of California, Santa Barbara)

Read More