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Impulse Technologies
                                      Beacons U to World of technology
        044-42133143, 98401 03301,9841091117 ieeeprojects@yahoo.com www.impulse.net.in
               A Hybrid Approach to Private Record Matching
   Abstract—
         Real-world entities are not always represented by the same set of features in
   different data sets. Therefore, matching records of the same real-world entity
   distributed across these data sets is a challenging task. If the data sets contain
   private information, the problem becomes even more difficult. Existing solutions
   to this problem generally follow two approaches: sanitization techniques and
   cryptographic techniques. We propose a hybrid technique that combines these two
   approaches and enables users to trade off between privacy, accuracy, and cost. Our
   main contribution is the use of a blocking phase that operates over sanitized data to
   filter out in a privacy-preserving manner pairs of records that do not satisfy the
   matching condition. We also provide a formal definition of privacy and prove that
   the participants of our protocols learn nothing other than their share of the result
   and what can be inferred from their share of the result, their input and sanitized
   views of the input data sets (which are considered public information). Our method
   incurs considerably lower costs than cryptographic techniques and yields
   significantly more accurate matching results compared to sanitization techniques,
   even when privacy requirements are high.




  Your Own Ideas or Any project from any company can be Implemented
at Better price (All Projects can be done in Java or DotNet whichever the student wants)
                                                                                          1

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48

  • 1. Impulse Technologies Beacons U to World of technology 044-42133143, 98401 03301,9841091117 ieeeprojects@yahoo.com www.impulse.net.in A Hybrid Approach to Private Record Matching Abstract— Real-world entities are not always represented by the same set of features in different data sets. Therefore, matching records of the same real-world entity distributed across these data sets is a challenging task. If the data sets contain private information, the problem becomes even more difficult. Existing solutions to this problem generally follow two approaches: sanitization techniques and cryptographic techniques. We propose a hybrid technique that combines these two approaches and enables users to trade off between privacy, accuracy, and cost. Our main contribution is the use of a blocking phase that operates over sanitized data to filter out in a privacy-preserving manner pairs of records that do not satisfy the matching condition. We also provide a formal definition of privacy and prove that the participants of our protocols learn nothing other than their share of the result and what can be inferred from their share of the result, their input and sanitized views of the input data sets (which are considered public information). Our method incurs considerably lower costs than cryptographic techniques and yields significantly more accurate matching results compared to sanitization techniques, even when privacy requirements are high. Your Own Ideas or Any project from any company can be Implemented at Better price (All Projects can be done in Java or DotNet whichever the student wants) 1