Utility preserving query log anonymization via semantic microaggregation

Batet, Montserrat; Erola, Arnau; Sánchez, David; Castellà‐Roca, Jordi

doi:10.1016/j.ins.2013.04.020

Cited by 34 publications

(20 citation statements)

References 42 publications

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“…There are different strategies to achieve this goal in the literature [20,[29][30][31], and we also have found in recent publications very similar approaches to the ones we had presented for the development of DisPA [32,33]. This shows a common interest of the research community towards the development of protocols that strive for a trade-off between utility and privacy in web search.…”

Section: Related Worksupporting

confidence: 67%

DisPA: An Intelligent Agent for Private Web Search

Juárez

Torra

2014

Studies in Computational Intelligence

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Abstract. Search queries can be used to infer preferences and interests of users. While search engines use this information for, among others, targeted advertising and personalization, these tasks can violate user's privacy. In 2006, after AOL disclosed the search queries of 650,000 users and some of them were re-identified, many Privacy Enhancement Technologies (PETs) have sought to solve this problem. The Dissociating Privacy Agent (DisPA), is a browser extension that acts as a proxy between the user and the search engine and semantically dissociates queries on real time. We show that DisPA increases the privacy of the user and hinders re-identification. We also propose an algorithm to measure and evaluate the privacy properties offered by DisPA.

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Section: Related Worksupporting

confidence: 67%

DisPA: An Intelligent Agent for Private Web Search

Juárez

Torra

2014

Studies in Computational Intelligence

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“…Batet et al in [8] present a query anonymization method based on semantic micro aggregation which focuses on reducing the risk of query log disclosure while retaining the utility of the query logs at the same time. In this approach, the semantic concepts of the query logs are retrieved from Open Data Project.…”

Section: Related Workmentioning

confidence: 99%

A Novel Query Obfuscation Scheme with User Controlled Privacy and Personalization

Punagin¹,

Arya²

2017

IJCA

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Web Search Engines are tools that help users find information. These search engines use the information provided by users, in terms of their search history to build their "user profiles". Rich user profiles enable the search engines to provide better personalized search results. However, this puts the user's privacy at risk. Apart from the risk of exposing one's identity, there is the added disadvantage of being subjected to unsolicited advertising and potential disclosure of sensitive information. Rich user profiles contain a lot of personally identifiable information, which can attract unwarranted malicious interests. It is important that sensitive data collection be curbed or at least obfuscated at the source. To that effect this work is a novel approach towards providing a balance between privacy preservation and personalization by keeping the user in control of his privacy Vs personalization decisions. This work supports complex queries and obfuscates them by adding a set of fake queries that are semantically related to the original query where both the semantic distance and the number of fake queries are user controlled parameters.

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“…Then, the relevance Re(q, e j ) between the concept e j and the query q is defined as the number of the titles of the concept e j that appear in the query q, i.e., Re(q, e j ) = |T (q) ∩ T (e j )|. (5) Let E(p i ) denote a set of concepts which belong to a topic p i , namely, each concept in E(p i ) is reachable to the topic p i along the categorization system of Wikipedia. Let depth(e j , p i ) denote the length of the shortest path from a concept e j to a topic p i in the categorization system of Wikipedia.…”

Section: Identifying User Intentionmentioning

confidence: 99%

“…It has been pointed out in [2,4] that the problem of disclosing user query intentions cannot be solved by using an anonymization scheme (e.g., those in [5,6]) to process a query log. For example, in 2006, AOL released an anonymized query log of around hundreds of thousands of randomly selected users [1,7].…”

Section: Introductionmentioning

confidence: 99%

Constructing plausible innocuous pseudo queries to protect user query intention

Shi

et al. 2015

Information Sciences

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Utility preserving query log anonymization via semantic microaggregation

Cited by 34 publications

References 42 publications

DisPA: An Intelligent Agent for Private Web Search

DisPA: An Intelligent Agent for Private Web Search

A Novel Query Obfuscation Scheme with User Controlled Privacy and Personalization

Constructing plausible innocuous pseudo queries to protect user query intention

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