Privacy Protection in Personalized Web Search Using Software Applications – Tools and Plug-Ins

Kumar, Krishan; Gupta, Mukesh Kumar; Jaglan, Vivek

doi:10.2139/ssrn.3884638

Cited by 2 publications

(2 citation statements)

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“…Privacy-enhancing PWS which has been involved in the creation of the hierarchical user profile, primarily based on the personal interests of the users because most of the users do not want to share private information with the search engine. This technique does not support the concept of run time profiling which is considered a big drawback (4,5) . A generalized offline user profile is created only once, and it is used for every query without making any changes in it.…”

Section: Introductionmentioning

confidence: 99%

“…At the same time, the web server is susceptible to assaults such as URL manipulations, which compromise the privacy of the user. To avoid this kind of assault, it would be sensible to utilise Homomorphism Encryption (HE), which combines data encryption with privacy protection, to create a new method (5,8,9) . That's why attempts are made to incorporate the HE request for privacy protection into tailored online searches.…”

Section: Introductionmentioning

confidence: 99%

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Homomorphic Encryption Based Privacy Protection for Personalised Web Search

Kumar¹,

Gupta²,

Saxena³

et al. 2022

IJST

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Objective: Privacy of user information in web search applications is traded off with quality of search results generated for a query by web search engine. In this article, we have developed a novel model utilizing Homomorphic Encryption for privacy protection of the user without compromising the quality of search results and response time. Methods: Response time is calculated using the GreedyDP and GreedyIL techniques, which is critical since encryption is usually followed by complicated calculations. Using the Homomorphic Encryption (HE) technique the user request is encrypted, rendering it unreadable or interpretable by eavesdroppers. Although the server will be unable to decode the requests, it will be possible to process those using algorithms and computations. The suggested model was utilized to evaluate the reaction time performance of four distinct current HE techniques. Findings: From the proposed model, it is inferred that, the performance of Gentry HE is superior to others since it takes 6% less time than its nearest competitor Paillier. Implementations show that the developed model, query encryption, does not create response delays and so supports the framework. Novelty: This research proposes a new PWS model with HE to increase data security and privacy in online search applications. The suggested study uses the GreedyDP and GreedyIL new methodologies.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%