7,176 research outputs found
Towards Practical Oblivious RAM
We take an important step forward in making Oblivious RAM (O-RAM) practical.
We propose an O-RAM construction achieving an amortized overhead of 20X-35X
(for an O-RAM roughly 1 terabyte in size), about 63 times faster than the best
existing scheme. On the theoretic front, we propose a fundamentally novel
technique for constructing Oblivious RAMs: specifically, we partition a bigger
O-RAM into smaller O-RAMs, and employ a background eviction technique to
obliviously evict blocks from the client-side cache into a randomly assigned
server-side partition. This novel technique is the key to achieving the gains
in practical performance
DivORAM: Towards a practical oblivious RAM with variable block size
Oblivious RAM (ORAM) is important for applications that require hiding access patterns. Many ORAM schemes have been proposed but most of them support only storing blocks of the same size. For the variable length data blocks, they usually fill them upto the same length before uploading, which leads to an increase in storage space and network bandwidth usage. To develop the first practical ORAM with variable block size, we proposed the “DivORAM” by remodeling the tree-based ORAM structure. It employs an additively homomorphic encryption scheme (Damgård–Jurik cryptosystem) executing at the server side to save the client computing overhead and the network bandwidth cost. As a result, it saves network bandwidth 30% comparing with Ring ORAM and 40% comparing with HIRB ORAM. Experiment results show that the response time of DivORAM is 10 × improved over Ring ORAM for practical parameters
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
What Storage Access Privacy is Achievable with Small Overhead?
Oblivious RAM (ORAM) and private information retrieval (PIR) are classic
cryptographic primitives used to hide the access pattern to data whose storage
has been outsourced to an untrusted server. Unfortunately, both primitives
require considerable overhead compared to plaintext access. For large-scale
storage infrastructure with highly frequent access requests, the degradation in
response time and the exorbitant increase in resource costs incurred by either
ORAM or PIR prevent their usage. In an ideal scenario, a privacy-preserving
storage protocols with small overhead would be implemented for these heavily
trafficked storage systems to avoid negatively impacting either performance
and/or costs. In this work, we study the problem of the best $\mathit{storage\
access\ privacy}\mathit{small\ overhead}\mathit{differential\ privacy\ access}\mathit{oblivious\ access}\epsilon = \Omega(\log n)\epsilon = \Theta(\log n)O(1)\epsilon = \Theta(\log n)O(\log\log n)$
overhead. This construction uses a new oblivious, two-choice hashing scheme
that may be of independent interest.Comment: To appear at PODS'1
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
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