1,465 research outputs found
A Simple Recursive Tree Oblivious RAM
Oblivious RAM (ORAM) has received increasing attention in the past few years. The goal of oblivious RAM is to enable a client, that can locally store only a small (preferably constant) amount of data, to store remotely N data items, and access them while hiding the identities of the items that are being accessed. Most of the earlier ORAM constructions were based on the hierarchical data structure of Goldreich and Ostrovsky. Shi et al. introduced a binary tree ORAM, which is simpler and more efficient than the classical hierarchical ORAM. Gentry et al. have improved the scheme. In this work, we improve these two constructions. Our scheme asymptotically outperforms all previous tree based ORAM schemes that have constant client memory, with an overhead of O(log^{2+eps}(N) * log^2(log(N))) per operation for a O(N) storage server. Although the best known asymptotic
result for ORAM is due to the hierarchical structure of Kushilevitz et al. (O(log^2(N)/log(log(N)))), tree based ORAM constructions are much simple
Path ORAM: An Extremely Simple Oblivious RAM Protocol
We present Path ORAM, an extremely simple Oblivious RAM protocol with a small
amount of client storage. Partly due to its simplicity, Path ORAM is the most
practical ORAM scheme known to date with small client storage. We formally
prove that Path ORAM has a O(log N) bandwidth cost for blocks of size B =
Omega(log^2 N) bits. For such block sizes, Path ORAM is asymptotically better
than the best known ORAM schemes with small client storage. Due to its
practicality, Path ORAM has been adopted in the design of secure processors
since its proposal
Deterministic, Stash-Free Write-Only ORAM
Write-Only Oblivious RAM (WoORAM) protocols provide privacy by encrypting the
contents of data and also hiding the pattern of write operations over that
data. WoORAMs provide better privacy than plain encryption and better
performance than more general ORAM schemes (which hide both writing and reading
access patterns), and the write-oblivious setting has been applied to important
applications of cloud storage synchronization and encrypted hidden volumes. In
this paper, we introduce an entirely new technique for Write-Only ORAM, called
DetWoORAM. Unlike previous solutions, DetWoORAM uses a deterministic,
sequential writing pattern without the need for any "stashing" of blocks in
local state when writes fail. Our protocol, while conceptually simple, provides
substantial improvement over prior solutions, both asymptotically and
experimentally. In particular, under typical settings the DetWoORAM writes only
2 blocks (sequentially) to backend memory for each block written to the device,
which is optimal. We have implemented our solution using the BUSE (block device
in user-space) module and tested DetWoORAM against both an encryption only
baseline of dm-crypt and prior, randomized WoORAM solutions, measuring only a
3x-14x slowdown compared to an encryption-only baseline and around 6x-19x
speedup compared to prior work
Data-Oblivious Graph Algorithms in Outsourced External Memory
Motivated by privacy preservation for outsourced data, data-oblivious
external memory is a computational framework where a client performs
computations on data stored at a semi-trusted server in a way that does not
reveal her data to the server. This approach facilitates collaboration and
reliability over traditional frameworks, and it provides privacy protection,
even though the server has full access to the data and he can monitor how it is
accessed by the client. The challenge is that even if data is encrypted, the
server can learn information based on the client data access pattern; hence,
access patterns must also be obfuscated. We investigate privacy-preserving
algorithms for outsourced external memory that are based on the use of
data-oblivious algorithms, that is, algorithms where each possible sequence of
data accesses is independent of the data values. We give new efficient
data-oblivious algorithms in the outsourced external memory model for a number
of fundamental graph problems. Our results include new data-oblivious
external-memory methods for constructing minimum spanning trees, performing
various traversals on rooted trees, answering least common ancestor queries on
trees, computing biconnected components, and forming open ear decompositions.
None of our algorithms make use of constant-time random oracles.Comment: 20 page
Optimal Hierarchical Layouts for Cache-Oblivious Search Trees
This paper proposes a general framework for generating cache-oblivious
layouts for binary search trees. A cache-oblivious layout attempts to minimize
cache misses on any hierarchical memory, independent of the number of memory
levels and attributes at each level such as cache size, line size, and
replacement policy. Recursively partitioning a tree into contiguous subtrees
and prescribing an ordering amongst the subtrees, Hierarchical Layouts
generalize many commonly used layouts for trees such as in-order, pre-order and
breadth-first. They also generalize the various flavors of the van Emde Boas
layout, which have previously been used as cache-oblivious layouts.
Hierarchical Layouts thus unify all previous attempts at deriving layouts for
search trees.
The paper then derives a new locality measure (the Weighted Edge Product)
that mimics the probability of cache misses at multiple levels, and shows that
layouts that reduce this measure perform better. We analyze the various degrees
of freedom in the construction of Hierarchical Layouts, and investigate the
relative effect of each of these decisions in the construction of
cache-oblivious layouts. Optimizing the Weighted Edge Product for complete
binary search trees, we introduce the MinWEP layout, and show that it
outperforms previously used cache-oblivious layouts by almost 20%.Comment: Extended version with proofs added to the appendi
The Cost of Address Translation
Modern computers are not random access machines (RAMs). They have a memory
hierarchy, multiple cores, and virtual memory. In this paper, we address the
computational cost of address translation in virtual memory. Starting point for
our work is the observation that the analysis of some simple algorithms (random
scan of an array, binary search, heapsort) in either the RAM model or the EM
model (external memory model) does not correctly predict growth rates of actual
running times. We propose the VAT model (virtual address translation) to
account for the cost of address translations and analyze the algorithms
mentioned above and others in the model. The predictions agree with the
measurements. We also analyze the VAT-cost of cache-oblivious algorithms.Comment: A extended abstract of this paper was published in the proceedings of
ALENEX13, New Orleans, US
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