Publication Type

Journal Article

Publication Date

2-2010

Abstract

Users of online services are increasingly wary that their activities could disclose confidential information on their business or personal activities. It would be desirable for an online document service to perform text retrieval for users, while protecting the privacy of their activities. In this article, we introduce a privacy-preserving, similarity-based text retrieval scheme that (a) prevents the server from accurately reconstructing the term composition of queries and documents, and (b) anonymizes the search results from unauthorized observers. At the same time, our scheme preserves the relevance-ranking of the search server, and enables accounting of the number of documents that each user opens. The effectiveness of the scheme is verified empirically with two real text corpora.

Keywords

Privacy of search queries, Security in text retrieval, Singular value decomposition

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Research Areas

Data Management and Analytics

Publication

ACM Transactions on Internet Technology

Volume

10

Issue

1

ISSN

1533-5399

Identifier

10.1145/1667067.1667071

Publisher

ACM

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://doi.org/10.1145/1667067.1667071

Comments

Article No.: 4

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