Anrin Chakraborti (Stony Brook University), Adam J. Aviv (United States Naval Academy), Seung Geol Choi (United States Naval Academy), Travis Mayberry (United States Naval Academy), Daniel S. Roche (United States Naval Academy), Radu Sion (Stony Brook University)

Oblivious RAM protocols (ORAMs) allow a client to access data from an untrusted storage device without revealing to that device any information about their access pattern. Typically this is accomplished through random shuffling of the data such that the storage device cannot determine where individual blocks are located, resulting in a highly randomized access pattern. Storage devices however, are typically optimized for sequential access. A large number of random disk seeks during standard ORAM operation induce a substantial overhead.

In this paper, we introduce rORAM, an ORAM specifically suited for accessing ranges of sequentially logical blocks while minimizing the number of random physical disk seeks. rORAM obtains significantly better asymptotic efficiency than prior designs (Asharov et al., ePrint 2017, Demertzis et al., CRYPTO 2018) reducing both the number of seeks and communication complexity by a multiplicative factor of $mathbb{O}(log N)$. An rORAM prototype is 30-50x times faster than Path ORAM for similar range-query workloads on local HDDs, 30x faster for local SSDs, and 10x faster for network block devices. rORAM's novel disk layout can also speed up standard ORAM constructions, e.g., resulting in a 2x faster Path ORAM variant. Importantly, experiments demonstrate suitability for real world applications -- rORAM is up to 5x faster running a file server and up to 11x faster running a range-query intensive video server workloads compared to standard Path ORAM.

View More Papers

NIC: Detecting Adversarial Samples with Neural Network Invariant Checking

Shiqing Ma (Purdue University), Yingqi Liu (Purdue University), Guanhong Tao (Purdue University), Wen-Chuan Lee (Purdue University), Xiangyu Zhang (Purdue University)

Read More

Enemy At the Gateways: Censorship-Resilient Proxy Distribution Using Game...

Milad Nasr (University of Massachusetts Amherst), Sadegh Farhang (Pennsylvania State University), Amir Houmansadr (University of Massachusetts Amherst), Jens Grossklags (Technical University of Munich)

Read More

Measurement and Analysis of Hajime, a Peer-to-peer IoT Botnet

Stephen Herwig (University of Maryland), Katura Harvey (University of Maryland, Max Planck Institute for Software Systems (MPI-SWS)), George Hughey (University of Maryland), Richard Roberts (University of Maryland, Max Planck Institute for Software Systems (MPI-SWS)), Dave Levin (University of Maryland)

Read More