Privacy-preserving reachability query services for sparse graphs

Peipei Yi; Zhe Fan; Shuxiang Yin

doi:10.1109/ICDEW.2014.6818298

Privacy-preserving reachability query services for sparse graphs

Peipei Yi
, Zhe Fan
, Shuxiang Yin

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

16 Citations (Scopus)

Abstract

This paper studies privacy-preserving query services for reachability queries under the paradigm of data outsourcing. Specifically, graph data have been outsourced to a third-party service provider (SP), query clients submit their queries to the SP, and the SP returns the query answers. However, SP may not always be trustworthy. Therefore, this paper considers protecting the structural information of the graph data and the query answers from the SP. This paper proposes simple yet optimized privacy-preserving 2-hop labeling. In particular, this paper proposes that the encrypted intermediate results of encrypted query evaluation are indistinguishable. The proposed technique is secure under chosen plaintext attack. We perform an experimental study on the effectiveness of the proposed techniques on both real-world and synthetic datasets.

Original language	English
Title of host publication	2014 IEEE 30th International Conference on Data Engineering Workshops, ICDEW 2014
Publisher	IEEE
Pages	32-35
Number of pages	4
ISBN (Electronic)	9781479934812
ISBN (Print)	9781479934805
DOIs	https://doi.org/10.1109/ICDEW.2014.6818298
Publication status	Published - 31 Mar 2014
Event	30th IEEE International Conference on Data Engineering Workshops, ICDEW 2014 - Chicago, IL, United States Duration: 31 Mar 2014 → 4 Apr 2014 https://ieeexplore.ieee.org/xpl/conhome/6811047/proceeding

Publication series

Name	Proceedings - International Conference on Data Engineering
ISSN (Print)	1084-4627

Conference

Conference	30th IEEE International Conference on Data Engineering Workshops, ICDEW 2014
Country/Territory	United States
City	Chicago, IL
Period	31/03/14 → 4/04/14
Internet address	https://ieeexplore.ieee.org/xpl/conhome/6811047/proceeding

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ICDEW.2014.6818298

Cite this

@inproceedings{e594a774423b4285911eea0111dc04f5,

title = "Privacy-preserving reachability query services for sparse graphs",

abstract = "This paper studies privacy-preserving query services for reachability queries under the paradigm of data outsourcing. Specifically, graph data have been outsourced to a third-party service provider (SP), query clients submit their queries to the SP, and the SP returns the query answers. However, SP may not always be trustworthy. Therefore, this paper considers protecting the structural information of the graph data and the query answers from the SP. This paper proposes simple yet optimized privacy-preserving 2-hop labeling. In particular, this paper proposes that the encrypted intermediate results of encrypted query evaluation are indistinguishable. The proposed technique is secure under chosen plaintext attack. We perform an experimental study on the effectiveness of the proposed techniques on both real-world and synthetic datasets.",

author = "Peipei Yi and Zhe Fan and Shuxiang Yin",

note = "Publisher copyright: {\textcopyright} 2014 IEEE; 30th IEEE International Conference on Data Engineering Workshops, ICDEW 2014 ; Conference date: 31-03-2014 Through 04-04-2014",

year = "2014",

month = mar,

day = "31",

doi = "10.1109/ICDEW.2014.6818298",

language = "English",

isbn = "9781479934805",

series = "Proceedings - International Conference on Data Engineering",

publisher = "IEEE",

pages = "32--35",

booktitle = "2014 IEEE 30th International Conference on Data Engineering Workshops, ICDEW 2014",

address = "United States",

url = "https://ieeexplore.ieee.org/xpl/conhome/6811047/proceeding",

}

Yi, P, Fan, Z & Yin, S 2014, Privacy-preserving reachability query services for sparse graphs. in 2014 IEEE 30th International Conference on Data Engineering Workshops, ICDEW 2014. Proceedings - International Conference on Data Engineering, IEEE, pp. 32-35, 30th IEEE International Conference on Data Engineering Workshops, ICDEW 2014, Chicago, IL, United States, 31/03/14. https://doi.org/10.1109/ICDEW.2014.6818298

Privacy-preserving reachability query services for sparse graphs. / Yi, Peipei; Fan, Zhe; Yin, Shuxiang.
2014 IEEE 30th International Conference on Data Engineering Workshops, ICDEW 2014. IEEE, 2014. p. 32-35 (Proceedings - International Conference on Data Engineering).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Privacy-preserving reachability query services for sparse graphs

AU - Yi, Peipei

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N2 - This paper studies privacy-preserving query services for reachability queries under the paradigm of data outsourcing. Specifically, graph data have been outsourced to a third-party service provider (SP), query clients submit their queries to the SP, and the SP returns the query answers. However, SP may not always be trustworthy. Therefore, this paper considers protecting the structural information of the graph data and the query answers from the SP. This paper proposes simple yet optimized privacy-preserving 2-hop labeling. In particular, this paper proposes that the encrypted intermediate results of encrypted query evaluation are indistinguishable. The proposed technique is secure under chosen plaintext attack. We perform an experimental study on the effectiveness of the proposed techniques on both real-world and synthetic datasets.

AB - This paper studies privacy-preserving query services for reachability queries under the paradigm of data outsourcing. Specifically, graph data have been outsourced to a third-party service provider (SP), query clients submit their queries to the SP, and the SP returns the query answers. However, SP may not always be trustworthy. Therefore, this paper considers protecting the structural information of the graph data and the query answers from the SP. This paper proposes simple yet optimized privacy-preserving 2-hop labeling. In particular, this paper proposes that the encrypted intermediate results of encrypted query evaluation are indistinguishable. The proposed technique is secure under chosen plaintext attack. We perform an experimental study on the effectiveness of the proposed techniques on both real-world and synthetic datasets.

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PB - IEEE

T2 - 30th IEEE International Conference on Data Engineering Workshops, ICDEW 2014

Y2 - 31 March 2014 through 4 April 2014

ER -

Privacy-preserving reachability query services for sparse graphs

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