REARGUARD: Secure Keyword Search Using Trusted Hardware

Sun, Wen‐Yih; Zhang, Ruide; Lou, Wenjing; Hou, Y. Thomas

doi:10.1109/infocom.2018.8485838

Cited by 24 publications

(24 citation statements)

References 16 publications

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“…State-of-the-art Hardware-Supported Oblivious Search Platforms. Existing systems [25,73] require secure hardware (e.g., Intel SGX) to process the entire outsourced data (e.g., encryption/decryption) for each search query to completely hide the access pattern. Unfortunately, this approach might also incur a high delay when dealing with a large amount of outsourced data since its cost grows linearly with the database size.…”

Section: Motivationmentioning

confidence: 99%

Hardware-Supported ORAM in Effect: Practical Oblivious Search and Update on Very Large Dataset

Hoang

Ozmen

Jang

et al. 2018

Proceedings on Privacy Enhancing Technologies

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The ability to query and update over encrypted data is an essential feature to enable breach-resilient cyber-infrastructures. Statistical attacks on searchable encryption (SE) have demonstrated the importance of sealing information leaks in access patterns. In response to such attacks, the community has proposed the Oblivious Random Access Machine (ORAM). However, due to the logarithmic communication overhead of ORAM, the composition of ORAM and SE is known to be costly in the conventional client-server model, which poses a critical barrier toward its practical adaptations. In this paper, we propose a novel hardware-supported privacy-enhancing platform called Practical Oblivious Search and Update Platform (POSUP), which enables oblivious keyword search and update operations on large datasets with high efficiency. We harness Intel SGX to realize efficient oblivious data structures for oblivious search/update purposes. We implemented POSUP and evaluated its performance on a Wikipedia dataset containing ≥229 keyword-file pairs. Our implementation is highly efficient, taking only 1 ms to access a 3 KB block with Circuit-ORAM. Our experiments have shown that POSUP offers up to 70× less end-to-end delay with 100× reduced network bandwidth consumption compared with the traditional ORAM-SE composition without secure hardware. POSUP is also at least 4.5× faster for up to 99.5% of keywords that can be searched compared with state-of-the-art Intel SGX-assisted search platforms.

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Section: Motivationmentioning

confidence: 99%

Hardware-Supported ORAM in Effect: Practical Oblivious Search and Update on Very Large Dataset

Hoang

Ozmen

Jang

et al. 2018

Proceedings on Privacy Enhancing Technologies

View full text Add to dashboard Cite

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“…Sun et al 190 utilized Intel SGX and AMD memory encryption for secure computation such that even if the software is untrusted, a secure computation can still be performed. The proposed scheme is able to offer better query expressiveness while maintaining query privacy.…”

mentioning

confidence: 99%

“…Hardware-based 48,190,[192][193][194] searchable encryption is software-based implementation, where the functionality is incorporated in the underlying protocol, and researchers have proposed numerous methods such as pseudorandom functions and generators, homomorphic encryption, inner product similarity, hash functions, bilinear maps, etc (discussed in Section 3.6). These schemes rely on using cryptography and theoretical proofs of the proposed algorithmic designs.…”

mentioning

confidence: 99%

“…These software-based solutions suffer from the following limitations. 190 1. The software-based solutions rely on the existing cryptographic primitives, the structure of the index, and the algorithm used and, hence, are limited in the functionalities supported, ie, the type of queries supported.…”

mentioning

confidence: 99%

“…Santos et al 48 designed carefully such that information disclosure is avoided. 190 As an example, side-channel and cache channel attacks need to be analyzed in Intel SGX through careful design of the system; else, the search behavior can be disclosed.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Searchable encryption: A survey on privacy‐preserving search schemes on encrypted outsourced data

Handa

Krishna

Aggarwal

2019

Concurrency and Computation

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Outsourcing confidential data to cloud storage leads to privacy challenges that can be reduced using encryption. However, with encryption in place, the utilization of the data is reduced, which leads to reduced quality of experience of the users. To overcome this, searchable encryption (SE) schemes are utilized, which allow the end users to retrieve the relevant documents from the cloud, for which various researchers have worked utilizing different techniques. Despite the popularity of the searchable encryption schemes, most of the surveys either do not provide or present an incomplete taxonomy of SE schemes. Hence, in this paper, we attempt to present a complete taxonomy/classification of the searchable encryption schemes in terms of the type of search, type of index, results retrieved, implementation type, multiplicity of users, and the technique used. From the literature, it is observed that inner product similarity is widely adopted by researchers to compute the similarity of the query and the document index as it provides both conjunctive and disjunctive searching (ie, have better search capability) but requires high search time (ie, have lower search efficiency). On the other hand, schemes based on binary comparisons exist, which require less search time (ie, have better search efficiency) but support only conjunctive searching (ie, have limited search capability). Thus, a major conclusion drawn from our work is that there is an imbalance between search capability and search efficiency, ie, in the existing schemes, search capability can be improved at the cost of search time only. Therefore, we suggest that one direction where researchers should work on is to provide a balance between search capability and search efficiency.

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A Secure Remote Monitoring Framework Supporting Efficient Fine-Grained Access Control and Data Processing in IoT

Chen

Sun

Zhang

et al. 2018

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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REARGUARD: Secure Keyword Search Using Trusted Hardware

Cited by 24 publications

References 16 publications

Hardware-Supported ORAM in Effect: Practical Oblivious Search and Update on Very Large Dataset

Hardware-Supported ORAM in Effect: Practical Oblivious Search and Update on Very Large Dataset

Searchable encryption: A survey on privacy‐preserving search schemes on encrypted outsourced data

A Secure Remote Monitoring Framework Supporting Efficient Fine-Grained Access Control and Data Processing in IoT

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