Liu, Liang and Wang, Rujia and Yang, Jun and Zhang, Youtao
(2019)
H-ORAM: A Cacheable ORAM Interface for Efficient I/O Accesses.
Master's Thesis, University of Pittsburgh.
(Unpublished)
Abstract
Oblivious RAM (ORAM) is an effective security primitive to prevent access pattern
leakage. By adding redundant memory accesses, ORAM prevents attackers from revealing the
patterns in the access sequences. However, ORAM tends to introduce a huge degradation on the
performance. With growing address space to be protected, ORAM has to store the majority of
data in the lower level storage, which further degrades the system performance.
In this paper, we propose Hybrid ORAM (H-ORAM), a novel ORAM primitive to address
large performance degradation when overflowing the user data to storage. H-ORAM consists of a
batch scheduling scheme for enhancing the memory bandwidth usage, and a novel ORAM
interface that returns data without waiting for the I/O access each time. We evaluate H-ORAM on
a real machine implementation. The experimental results show that that H-ORAM outperforms the
state-of-the-art Path ORAM by 19.8x for a small data set and 22.9x for a large data set.
Share
Citation/Export: |
|
Social Networking: |
|
Details
Item Type: |
University of Pittsburgh ETD
|
Status: |
Unpublished |
Creators/Authors: |
|
ETD Committee: |
|
Date: |
18 June 2019 |
Date Type: |
Publication |
Defense Date: |
4 March 2019 |
Approval Date: |
18 June 2019 |
Submission Date: |
5 April 2019 |
Access Restriction: |
No restriction; Release the ETD for access worldwide immediately. |
Number of Pages: |
44 |
Institution: |
University of Pittsburgh |
Schools and Programs: |
Swanson School of Engineering > Electrical and Computer Engineering |
Degree: |
MS - Master of Science |
Thesis Type: |
Master's Thesis |
Refereed: |
Yes |
Uncontrolled Keywords: |
ObliviousRAM,memorysecurity,I/Oaccesses,scheduling,obliviousshuffle |
Date Deposited: |
18 Jun 2019 17:45 |
Last Modified: |
18 Jun 2019 17:45 |
URI: |
http://d-scholarship.pitt.edu/id/eprint/36374 |
Metrics
Monthly Views for the past 3 years
Plum Analytics
Actions (login required)
|
View Item |