PRIVATE SEARCHING ON STREAMING DATA
BASED ON KEYWORD FREQUENCY
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ABSTRACT:
Private
searching on streaming data is a process to dispatch to a public server a
program, which searches streaming sources of data without revealing searching
criteria and then sends back a buffer containing the findings. From an Abelian
group homomorphic encryption, the searching criteria can be constructed by only
simple combinations of keywords, for example, disjunction of keywords. The
recent breakthrough in fully homomorphic encryption has allowed us to construct
arbitrary searching criteria theoretically. In this paper, we consider a new
private query, which searches for documents from streaming data on the basis of
keyword frequency, such that the frequency of a keyword is required to be
higher or lower than a given threshold. This form of query can help us in
finding more relevant documents. Based on the state of the art fully homomorphic
encryption techniques, we give disjunctive, conjunctive, and complement
constructions for private threshold queries based on keyword frequency.
Combining the basic constructions, we further present a generic construction
for arbitrary private threshold queries based on keyword frequency. Our protocols
are semantically secure as long as the underlying fully homomorphic encryption
scheme is semantically secure.
EXISTING SYSTEM:
THE
problem of private searching on streaming data was first introduced by
Ostrovsky and Skeith. It was motivated by one of the tasks of the intelligence
community, that is, how to collect potentially useful information from huge
volumes of streaming data flowing through a public server. However, that data
which is potentially useful and raises a red flag is often classified and
satisfies secret search criteria. The challenge is thus how to keep the search
criteria classified even if the program residing in the public server falls
into adversary’s hands. This problem has many applications for the purpose of
intelligence gathering. For example, in airports one can use this technique to
find if any Of hundreds of passenger lists has a name from a possible list of terrorists and, if so, to find
his/hers itinerary without revealing the secret terrorists list.
DISADVANTAGES OF
EXISTING SYSTEM:
v Streaming
data have not considered keyword frequency.
v
Results based on secret algorithms only.
v It
is based mainly on keyword frequency and link popularity.
PROPOSED
SYSTEM:
In
this paper, we consider a new private query, which searches for documents from
streaming data based on keyword frequency, such that a number of times that a
keyword appears in a matching document is required to be higher or lower than a
given threshold. For example, find documents containing keywords k1; k2; . . .
; kn such that the frequency of the keyword kiði ¼ 1; 2; . . . ; nÞ in the document
is higher (or lower) than ti. We take the lower case into account because terms
that appear too frequently are often not very useful as they may not allow one
to retrieve a small subset of documents from the streaming data.
ADVANTAGES OF PROPOSED
SYSTEM:
v
Using Keyword search algorithm.
v
Using KeyGen to introduce secret keys.
v
Arbitrary threshold query based on
keyword frequency.
SYSTEM CONFIGURATION:-
HARDWARE REQUIREMENTS:-
Processor - Pentium –IV
Speed - 1.1 Ghz
RAM - 512 MB(min)
Hard Disk - 40 GB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - LCD/LED
SOFTWARE
REQUIREMENTS:
Operating
system : Windows XP.
Coding
Language : .Net
Data
Base : SQL Server 2005
Tool : VISUAL STUDIO 2008.
REFERENCE:
Xun
Yi, Elisa Bertino, Fellow, IEEE, Jaideep Vaidya, and Chaoping Xing, “Private Searching on Streaming Data Based on Keyword Frequency”
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING, VOL. 11, NO. 2,
MARCH/APRIL 2014
