Using Personalized Web Search (PWS) we can
improve the quality of search results in the Internet. The
existing UPS based Personalized Web Searching has many
drawbacks. First, there may be a chance of eavesdropping
when generalized profile forwarded to the server. Second,
web server is vulnerable to web attacks like URL
manipulation attacks. The impact of these attacks will affect
user’s personal information. So we introduce a new
framework called UPES. Here, the data stored in the serverside
and request from user will be in encrypted form. Fully
Homomorphic Encryption over Integers (FHEI) is used for
encrypting data. The experimental results show that this
framework functioned in the best possible manner with the
least waste of time and effort.
Published In : IJCAT Journal Volume 2, Issue 8
Date of Publication : August 2015
Pages : 307 - 314
Figures :08
Tables : 04
Publication Link :Implementation of Privacy-Preserved Personalized
Web Search based on Fully Homomorphic Encryption
over Integers
Akhila G S : Department of Computer Science and Engineering, Mohandas College of Engineering and Technology, Anad
Thiruvananthapuaram, Kerala 695544, India
Prasanth R S : Assistant Professor, Department of Computer Science and Engineering, Mohandas College of Engineering and Technology, Anad
Thiruvananthapuaram, Kerala 695544, India
Personalized Web Search
UPS
User Profile
Generalized User Profile
FHEI
This thesis work provides a client-side and server-side
privacy protection framework called UPES for
personalized web search. In UPES, the server must
automatically protect the users’ privacy without
customizing privacy requirements by the user. Because,
here we applies Homomorphic encryption when request
sent to the server. So there is no problem occurs when an
eavesdropper gets this request. Since the encrypted data
are stored at server, we can protect web server from all
types of web attacks like URL manipulation attacks, trial
and error attacks, etc. Besides this encryption, we also
provide an authentication for server to protect it from
attacks. Here, users’ neither registers their personal
information’s nor customizes their privacy requirements.
Thus using this framework, we can completely protect
client-side and server-side privacy. The experimental
results show that this technique functioned in the best
possible manner with the least waste of time and effort.
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