Scoram

Wang, Xiao; Huang, Yan; Chan, T.-H. Hubert; Shelat, Abhi; Shi, Elaine

doi:10.1145/2660267.2660365

Cited by 117 publications

(8 citation statements)

References 34 publications

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“…Some recent work explores building an ORAM for secure multi-party computation (MPC) [35]. MPC is a powerful cryptographic primitive that allows multiple parties to perform rich data analytics over their private data while preserving each party's data privacy [36].…”

Section: Secure Multi-party Computationmentioning

confidence: 99%

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A Range Query Method for Data Access Pattern Protection Based on Uniform Access Frequency Distribution

Jin¹,

Zhao²,

Cheng³

et al. 2023

J-NaNA

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Data encryption is necessary to keep user information secure and private on the cloud. However, adversaries can still learn valuable information about the encrypted data by observing data access patterns. To solve this issue, Oblivious RAMs (ORAMs) are proposed to hide access patterns. However, ORAMs are expensive and not suitable for deployment in a large database. In this work, we propose a range query algorithm while providing data access pattern protection based on uniform access frequency. In the preprocessing, multiple key-value pairs in the database are grouped and stored in each storage module, and we make copies for frequently accessed key-value pairs and also add some dummy key-value pairs on each storage module. In the online query processing, according to the range query length of the received query access request, we visit the specific storage module for the query and obtain the query result. Based on the techniques above, our method makes the uniform distribution of access frequency of data blocks in the database and achieves a security guarantee as strong as the state-of-the-art method. Compared with data queries that do not provide data access pattern protection, the ratio of network communication overhead is constant rather than logarithmic in ORAMs.

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Section: Secure Multi-party Computationmentioning

confidence: 99%

“…That is to say, the problem setting in MPC is clearly different from our cloud database setting. Therefore, these MPC-based solutions [35]- [38] are designed for a different context and we do not evaluate them in our study.…”

Section: Secure Multi-party Computationmentioning

confidence: 99%

A Range Query Method for Data Access Pattern Protection Based on Uniform Access Frequency Distribution

Jin¹,

Zhao²,

Cheng³

et al. 2023

J-NaNA

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“…Other examples of cryptographic primitives for secure computation include Oblivious RAM (ORAM, [57,136]), homomorphic encryption (HE, [55]), and secret sharing (SS, [127]). ORAM-based approaches [46,89,148] build shared ORAM, and then data privacy is achieved by multiple rounds of interactions between the CPU and the shared memory. Since all these interactions are encrypted and the shared ORAM re-encrypts and shuffles the data whenever it is accessed, low efficiency becomes a major drawback.…”

Section: Introductionmentioning

confidence: 99%

A Survey of Secure Computation Using Trusted Execution Environments

Li¹,

Yang²,

Xiang³

et al. 2023

Preprint

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As an essential technology underpinning trusted computing, the trusted execution environment (TEE) allows one to launch computation tasks on both on-and off-premises data while assuring confidentiality and integrity. This article provides a systematic review and comparison of TEE-based secure computation protocols. We first propose a taxonomy that classifies secure computation protocols into three major categories, namely secure outsourced computation, secure distributed computation and secure multi-party computation. To enable a fair comparison of these protocols, we also present comprehensive assessment criteria with respect to four aspects: setting, methodology, security and performance. Based on these criteria, we review, discuss and compare the state-of-the-art TEE-based secure computation protocols for both general-purpose computation functions and special-purpose ones, such as privacy-preserving machine learning and encrypted database queries. To the best of our knowledge, this article is the first survey to review TEE-based secure computation protocols and the comprehensive comparison can serve as a guideline for selecting suitable protocols for deployment in practice. Finally, we also discuss several future research directions and challenges.CCS Concepts: • Security and privacy → Tamper-proof and tamper-resistant designs; Trust frameworks; Privacy-preserving protocols; Management and querying of encrypted data.

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“…This ORAM incurs an enormous overhead in bandwidth and processing time, which prevents any practical use of it. Fortunately, this first trivial ORAM was followed up by many ORAM constructions and improvements [6][7][8][9][10][11][12][13][14][15][16][17]. The basic idea in these new ORAMs, to make the data access oblivious, is to introduce an extra storage at the server and continuously and obliviously shuffle the data so that no data block is saved in its same previous location.…”

Section: Introductionmentioning

confidence: 99%

Locality Aware Path ORAM: Implementation, Experimentation and Analytical Modeling

Al-Saleh

Belghith

2018

Computers

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In this paper, we propose an advanced implementation of Path ORAM to hide the access pattern to outsourced data into the cloud. This implementation takes advantage of eventual data locality and popularity by introducing a small amount of extra storage at the client side. Two replacement strategies are used to manage this extra storage (cache): the Least Recently Used (LRU) and the Least Frequently Used (LFU). Using the same test bed, conducted experiments clearly show the superiority of the advanced implementation compared to the traditional Path ORAM implementation, even for a small cache size and reduced data locality. We then present a mathematical model that provides closed form solutions when data requests follow a Zipf distribution with non-null parameter. This model is showed to have a small and acceptable relative error and is then well validated by the conducted experimental results.

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Scoram

Cited by 117 publications

References 34 publications

A Range Query Method for Data Access Pattern Protection Based on Uniform Access Frequency Distribution

A Range Query Method for Data Access Pattern Protection Based on Uniform Access Frequency Distribution

A Survey of Secure Computation Using Trusted Execution Environments

Locality Aware Path ORAM: Implementation, Experimentation and Analytical Modeling

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