This document summarizes a project that proposes a privacy-preserving personalized web search framework called UPS. UPS allows users to specify customized privacy requirements for their hierarchical user profiles. It performs online generalization of user profiles for each query to balance personalization utility and privacy risk without compromising search quality or unnecessarily exposing user profiles. The framework consists of client and server components, with the client maintaining profiles and privacy specifications and handling query processing and result personalization.

1. Supporting Privacy Protection in
Personalized Web Search
Guided By:
Sri. Naveen Kumar B
Assistant Professor
CS & E Dept.
Project Members:
Ankita Bala 4UB11CS065
Mohammed Dawood 4UB11CS031
Nagesh M 4UB11CS068

2. Personalized 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.
We study privacy protection in PWS applications that model user preferences
as hierarchical user profiles.
We propose a PWS framework called UPS that can adaptively
generalize profiles by queries while respecting user specified privacy
requirements. Our runtime generalization aims at striking a balance between
two predictive metrics that evaluate the utility of personalization and the
privacy risk of exposing the generalized profile.
Abstract:-

3. THE web search engine has long become the most important portal
for ordinary people looking for useful information on the web.
However, users might experience failure when search engines return
irrelevant results that do not meet their real intentions.
Such irrelevance is largely due to the enormous variety of users’
contexts and backgrounds, as well as the ambiguity of texts.
Personalized web search (PWS) is a general category of search
techniques aiming at providing better search results, which are tailored for
individual user needs. As the expense, user information has to be collected
and analyzed to figure out the user intention behind the issued query.
Introduction

4. Disadvantage:
1. All the sensitive topics are detected using an absolute metric called
surprisal based on the information theory.
2. The existing profile-based PWS do not support runtime profiling.
3. The existing methods do not take into account the customization of privacy
requirements.
4. Personalization techniques require iterative user interactions when creating
personalized search results.
Problem Statement:-

5. This project proposes a privacy- preserving personalized web search
framework called UPS i.e User customizable Privacy- preserving Search, that
generalize profile for every query as per user privacy specification.
Based on personalization and privacy risk metric, this project
formulate Risk Profile Generation, with its NP- hardness proved. It develops
two simple but effective generalization algorithms, GreedyDP and GreedyIL,
to support runtime profiling. GreedyDP maximize the discriminating power
(DP) while GreedyIL minimize the information loss (IL).
This project also provide a mechanism for the client to decide
whether or not to personalize a query in UPS. This decision is made before
each runtime profiling to enhance the stability of the search results.
Solution Statement

6. It enhances the stability of the search quality.
It avoids the unnecessary exposure of the user profile.
 The framework allowed users to specify customized privacy
requirements via the hierarchical profiles. In addition, UPS
also performed online generalization on user profiles to
protect the personal privacy without compromising the
search quality..
Advantages:-

7. As shown in fig UPS consists of number of clients/users and a server for fulfilling
clients request. In clients machine, the online profiler is implemented as search proxy
which maintains users profile in hierarchy of nodes and also maintain the user
specified privacy requirement as a set of sensitive nodes. There are two phase,
namely Offline and Online phase for the framework. During Offline, a hierarchical
user profile is created and user specified privacy requirement is marked on it.The
query fired by user is handled in the online phase as:
Architectural Design:

8. When user fires a query on the client, proxy generates user profile in run time. The
output is generalized user profile considering the privacy requirements. Then, the
query along with generalized profile of user is sent to PWS server for personalized
web search. The search result is personalized and the response is sent back to query
proxy. Finally, the proxy presents the raw result or reranks them with user profile.
Architectural Design:

9. Module Design:
• Admin
View Info To Database Module.
Add Info To Database Module.
View User Profile Module.
• User
New User Registration.
Sign In.

10. Hardware Requirements
Processor : Pentium Iv 2.6 GHz
Memory : 512 Mb RAM
Hard Disk : 20 Gb
System Requirements:

11. Client on the Internet: Web Browser
Web Server: Glass fish
Database Server : MySQL Server 5.0
Database Connector : MySQL ODBC 5.1 Driver
Front End Designing : HTML , Cascading Style Sheet CSS
Dynamic web pages : Java Server pages JSP
Data Base Access Language : Java Data Base connectivity JDBC
Software Requirements:

12. This project presented a client-side privacy protection framework called
UPS for personalized web search. UPS could potentially be adopted by any PWS
that captures user profiles in a hierarchical taxonomy. The framework allowed
users to specify customized privacy requirements via the hierarchical profiles.
In addition, UPS also performed online generalization on user profiles to
protect the personal privacy without compromising the search quality.
Conclusion:

13. HTML - Rajesh Hongal
JSP Technology - Patrick Naughton
Web Technology - Renuka T Ambigar
Fundamentals Of Database System - Elmasri &Navathe
My-SQL - Kane George Coach
Bibliography:

14. Any Queries…..???