Results 161 to 170 of about 351,533 (201)
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Supporting Privacy Protection in Personalized Web Search
IEEE Transactions on Knowledge and Data Engineering, 2014Personalized web search (PWS) has demonstrated its effectiveness in improving the quality of various search services on the Internet. However, evidences show that users' reluctance to disclose their private information during search has become a major barrier for the wide proliferation of PWS.
null Lidan Shou +3 more
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Preserving user’s privacy in web search engines
Computer Communications, 2009Web search engines (e.g. Google, Yahoo, Microsoft Live Search, etc.) are widely used to find certain data among a huge amount of information in a minimal amount of time. However, these useful tools also pose a privacy threat to the users: web search engines profile their users by storing and analyzing past searches submitted by them.
Jordi Castellà-Roca +2 more
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Web Search Privacy Evaluation Metrics
2023Privacy quantification methods are used to quantify the knowledge the adverse search engine has obtained with and without privacy protection mechanisms. Thus, these methods calculate privacy exposure. Private web search techniques are based on many methods (e.g., proxy service, query modification, query exchange, and others). This variety of techniques
Rafi Ullah Khan +2 more
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Quantifying Web-Search Privacy
Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, 2014Web search queries reveal extensive information about users' personal lives to the search engines and Internet eavesdroppers. Obfuscating search queries through adding dummy queries is a practical and user-centric protection mechanism to hide users' search intentions and interests.
Arthur Gervais +4 more
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2012 Fourth International Conference on Ubiquitous and Future Networks (ICUFN), 2012
Since there are many sources of potentially identifying information in web search (e.g. IP address), we need to ways to hide major clues to the user's identity. Although there have been prior attempts to address this problem, all of them incur linear round complexity in the number of users.
null Myungsun Kim, null Jihye Kim
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Since there are many sources of potentially identifying information in web search (e.g. IP address), we need to ways to hide major clues to the user's identity. Although there have been prior attempts to address this problem, all of them incur linear round complexity in the number of users.
null Myungsun Kim, null Jihye Kim
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Towards efficient and accurate privacy preserving web search
Proceedings of the 9th Workshop on Middleware for Next Generation Internet Computing, 2014Querying Web search engines is by far the most frequent activity performed by online users and consequently the one in which they are likely to reveal a significant amount of personal information. Protecting the privacy of Web requesters is thus becoming increasingly important.
Petit, Albin +3 more
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Supporting Privacy Protection in Personalized Web Search
2021In web personalization and recommender systems, the main role is played by the Web Usage Mining. This paper has proposed an efficient recommender system depending upon the Web Usage Mining and ontology. The very first stage of this proposed method is mining the features from the web documents as well as creating the relevant idea. Then, the site builds
S. Vishnupriya +2 more
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Achieve Web Search Privacy by Obfuscation
2020After personal information of up to 87 million users of Facebook may be leaked to the consulting firm Cambridge Analysis in March 2018, some hackers sold 870 million user information stolen from 38 popular websites on the Darkweb in February 2019. The issue of privacy protection has once again received intense attention from people.
Hao Wang, Wenyan Liu, Jiangtao Wang
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Privacy-Enhanced Personalisation of Web Search
2015In personalised search, user information needs captured through cookies and Web search history for example, make it possible to infer personal or sensitive information about a person. Although prior studies have established sources of privacy leakage on the Web, there is a need for identifying the sources of data leakage concerning personalised search,
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