Knowledge-based scheme to create privacy-preserving but semantically-related queries for web search engines

Sánchez, David; Castellí-Roca, Jordi; Viejo, Alexandre

doi:10.1016/j.ins.2012.06.025

Cited by 55 publications

(40 citation statements)

References 33 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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“…GooPIR, [16], [17], attempts to disguise a user's "true" queries by adding masking keywords directly into a true query before submitting to a recommender system. Results are then filtered to extract items that are relevant to the user's original true query.…”

Section: Related Workmentioning

confidence: 99%

“…Comparison of PRI+ with alternative implementations was performed by taking results from Multinomial Naive Bayes (NB) and Linear SVM (SVM) classifiers to estimate the probabilities in the definition of M k in (17). The intent of the comparison is to determine which of the NB, PRI+ and SVM estimators detect privacy threats, using the definition of M k in (17), for test items previously labeled as "sensitive" by examining the topic of the query used.…”

Section: A Preliminariesmentioning

confidence: 99%

Plausible Deniability in Web Search—From Detection to Assessment

Aonghusa

Leith

2018

IEEE Trans.Inform.Forensic Secur.

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Abstract-Web personalisation uses what systems know about us to create content targeted at our interests. When unwanted personalisation suggests we are interested in sensitive or embarrassing topics a natural reaction is to deny interest. This is a practical response only if denial of our interest is credible or plausible. Adopting a definition of plausible deniability in the usual sense of "on the balance of probabilities", we develop a practical and scalable tool called PDE allowing a user to decide when their ability to plausibly deny interest in sensitive topics is compromised. We show that threats to plausible deniability are readily detectable for all topics tested in an extensive testing program. Of particular concern is observation of threats to deniability of interest in topics related to health and sexual preferences. We show this remains the case when attempting to disrupt search engine learning through noise query injection and click obfuscation. We design a defence technique exploiting uninteresting, proxy topics and show that it provides a more effective defence of plausible deniability in our experiments.

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“…Sanchez et al in [6], propose a mechanism where users are in control of the amount of private information they reveal vs. the degree of richness their user profiles retain. Their solution obfuscates the original query by adding "k" number of fake queries to the original query set.…”

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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Knowledge-based scheme to create privacy-preserving but semantically-related queries for web search engines

Cited by 55 publications

References 33 publications

DisPA: An Intelligent Agent for Private Web Search

DisPA: An Intelligent Agent for Private Web Search

Plausible Deniability in Web Search—From Detection to Assessment

A Novel Query Obfuscation Scheme with User Controlled Privacy and Personalization

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