International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 104 | Views: 383

Research Paper | Computer Science & Engineering | India | Volume 4 Issue 8, August 2015 | Popularity: 7 / 10


     

Privacy Preservation Protection for Personalized Web User by k-Anonymity with Profile Construction for Web Search Engines

Uma Maheswari.T, Dr.V. Kavitha


Abstract: Personalized Web Search (PWS) of each user is varied from common web search, since personalized web search of the each user is majorly relying on the queries submitted by user and their user interests with their information needs. Though, substantiation shows that users disinclination to reveal their private information throughout web search has become a most important barrier designed for the extensive proliferation of PWS. In order to overcome study to privacy protection in PWS relying on their user preferences in this work proposed a hierarchical tree structure for user profiles. Introduces a novel PWS framework named as User Customizable Online Privacy-preserving Search with K-anonymity (UCOPSK) with the intention of is able to adaptively simplify profiles with queries while regarding user specified privacy achievement in both online and offline searching. The proposed UCOPSK framework majorly consists of two phases as important like the offline and online phases, designed for each user. Throughout the offline phase, a hierarchical user profile is created and customized through the user-specified confidentiality requirements. K-anonymity is designed to each user to disclosure sensitive information of user, which is able to successfully prevent the information of each. K-anonymity additionally considers privacy for user through calculation K value. Experimentation evaluation results shows that the proposed UCOPSK achieves highest searching quality, less response time when compare to existing personalized search services, it shows that the proposed UCOPSK methods fully protect user privacy.


Keywords: Web search engines, Privacy protection, personalized web search, web mining, utility, risk, profile, generalization and K-anonymity


Edition: Volume 4 Issue 8, August 2015


Pages: 1640 - 1647



Make Sure to Disable the Pop-Up Blocker of Web Browser




Text copied to Clipboard!
Uma Maheswari.T, Dr.V. Kavitha, "Privacy Preservation Protection for Personalized Web User by k-Anonymity with Profile Construction for Web Search Engines", International Journal of Science and Research (IJSR), Volume 4 Issue 8, August 2015, pp. 1640-1647, https://www.ijsr.net/getabstract.php?paperid=SUB157714, DOI: https://www.doi.org/10.21275/SUB157714



Similar Articles

Downloads: 0

Survey Paper, Computer Science & Engineering, India, Volume 11 Issue 8, August 2022

Pages: 947 - 949

COVID-19 Prediction using Machine Learning Algorithms

Saily Suresh Patil

Share this Article

Downloads: 1 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1

Research Paper, Computer Science & Engineering, India, Volume 13 Issue 4, April 2024

Pages: 1127 - 1135

Generative Artificial Intelligence: Unveiling the Potential and Challenges

Brahmaleen Kaur Sidhu

Share this Article

Downloads: 1 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1

Analysis Study Research Paper, Computer Science & Engineering, India, Volume 13 Issue 7, July 2024

Pages: 1099 - 1104

Forecasting Health: Machine Learning Approaches to Disease Prediction

Nandana Santhosh, Prayag Tushar, Rohan Gilroy Gomez, Devanarayanan V

Share this Article

Downloads: 1 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1

Research Paper, Computer Science & Engineering, India, Volume 13 Issue 8, August 2024

Pages: 1758 - 1765

Enhancing Corporate Financial Performance Through AI: A Novel AI Model for Forecasting Organizational Risk Management, CRM, and Operational Efficiency

Mohammed Saleem Sultan, Mohammed Shahid Sultan

Share this Article

Downloads: 1 | Weekly Hits: ⮙1 | Monthly Hits: ⮙1

Research Paper, Computer Science & Engineering, India, Volume 13 Issue 10, October 2024

Pages: 1831 - 1836

Risk Assessment in Online Social Networks Through Client Activity Analysis using Machine Learning

Sanaboina Chandra Sekhar

Share this Article



Top