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Virginia Tech

Oblivious RAM in Scalable SGX

Abstract

dc:description.abstract

The prevalence of cloud storage has yielded significant benefits to consumers. Trusted Exe- cution Environments (TEEs) have been introduced to protect program execution and data in the cloud. However, an attacker targeting the cloud storage server through side-channel attacks can still learn some data in TEEs. This data retrieval is possible through the monitor- ing and analysis of the encrypted ciphertext as well as a program's memory access patterns. As the attacks grow in complexity and accuracy, innovative protection methods must be de- signed to secure data. This thesis proposes and implements an ORAM controller primitive in TEE and protects it from all potential side-channel attacks. This thesis presents two vari- ations, each with two different encryption methods designed to mitigate attacks targeting both memory access patterns and ciphertext analysis. The latency for enabling this protec- tion is calculated and proven to be 75.86% faster overall than the previous implementation on which this thesis is based.

Degree

thesis:*
Name thesis:degree_name
Master of Science
Level thesis:degree_level
masters
Discipline thesis:degree_discipline
Computer Engineering
Department dc:contributor.department
Electrical and Computer Engineering
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2024

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Marathe, Akhilesh Parag
Chair dc:contributor.committeechair
  • Xiong, Wenjie
Committee members dc:contributor.committeemember
  • Hoang, Thang
  • Wang, Haining

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • In Copyright
Language dc:language.iso
en

Identifiers

dc:identifier.*
Dc Identifier Other
vt_gsexam:41097
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/119324

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Marathe, Akhilesh Parag. Oblivious RAM in Scalable SGX. masters thesis, Virginia Tech, 2024. https://hdl.handle.net/10919/119324