Search (4 results, page 1 of 1)

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Abstract

In a digital library, book search is one of the most important information services. However, with the rapid development of network technologies such as cloud computing, the server-side of a digital library is becoming more and more untrusted; thus, how to prevent the disclosure of users' book query privacy is causing people's increasingly extensive concern. In this article, we propose to construct a group of plausible fake queries for each user book query to cover up the sensitive subjects behind users' queries. First, we propose a basic framework for the privacy protection in book search, which requires no change to the book search algorithm running on the server-side, and no compromise to the accuracy of book search. Second, we present a privacy protection model for book search to formulate the constraints that ideal fake queries should satisfy, that is, (i) the feature similarity, which measures the confusion effect of fake queries on users' queries, and (ii) the privacy exposure, which measures the cover-up effect of fake queries on users' sensitive subjects. Third, we discuss the algorithm implementation for the privacy model. Finally, the effectiveness of our approach is demonstrated by theoretical analysis and experimental evaluation.

Date

6. 1.2020 17:22:25

Type

a

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Abstract

In a digital library, an increasingly important problem is how to prevent the exposure of user privacy in an untrusted network. This study aims to design an effective approach for the protection of user privacy in a digital library, by consulting the basic ideas of encryption and anonymization. In our proposed approach, any privacy data, which can identify user's real identity, should be encrypted first before being submitted to the library server, to achieve anonymization of user identity. Then, to solve the problem of querying encrypted privacy data, additional feature data are constructed for the encrypted data, such that much of the query processing can be completed at the server-side, without decrypting the data, thereby improving the efficiency of each kind of user query operation. Both theoretical analysis and experimental evaluation demonstrate the effectiveness of the approach, which can improve the security of users' data privacy and behavior privacy on the untrusted server-side, without compromising the availability (i.?e. accuracy, efficiency, and usability) of digital library services. This paper provides a valuable study attempt at the protection of digital library users' privacy, which has a positive influence on the development of a privacy-preserving library in an untrusted network environment.

Type

a

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Abstract

This paper reviews a large number of research achievements relevant to user privacy protection in an untrusted network environment, and then analyzes and evaluates their application limitations in personalized information retrieval, to establish the conditional constraints that an effective approach for user preference privacy protection in personalized information retrieval should meet, thus providing a basic reference for the solution of this problem. First, based on the basic framework of a personalized information retrieval platform, we establish a complete set of constraints for user preference privacy protection in terms of security, usability, efficiency, and accuracy. Then, we comprehensively review the technical features for all kinds of popular methods for user privacy protection, and analyze their application limitations in personalized information retrieval, according to the constraints of preference privacy protection. The results show that personalized information retrieval has higher requirements for users' privacy protection, i.e., it is required to comprehensively improve the security of users' preference privacy on the untrusted server-side, under the precondition of not changing the platform, algorithm, efficiency, and accuracy of personalized information retrieval. However, all kinds of existing privacy methods still cannot meet the above requirements. This paper is an important study attempt to the problem of user preference privacy protection of personalized information retrieval, which can provide a basic reference and direction for the further study of the problem.

Type

a

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Type

a