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Secure Mining of Association Rules in HorizontallyDistributed Databases
03-18-2015, 06:28 PM
#
Secure Mining of Association Rules in HorizontallyDistributed Databases
Abstract
We propose a protocol for secure mining of association rules in horizontally distributed databases. Our protocol, like theirs, is based on the Fast Distributed Mining (FDM) algorithm which is an unsecured distributed version of the Apriori algorithm.
The main ingredients in our protocol are two novel secure multi-party algorithms — one that computes the union of private subsets that each of the interacting players hold, and another that tests the inclusion of an element held by one player in a subset held by another. Our protocol offers enhanced privacy with respect to the protocol. In addition, it is simpler and is significantly more efficient in terms of communication rounds, communication cost and computational cost.

Existing System

In Existing System, the problem of secure mining of association rules in horizontally partitioned databases. In that setting, there are several sites (or players) that hold homogeneous databases, i.e., databases that share the same schema but hold information on different entities. The inputs are the partial databases, and the required output is the list of association rules that hold in the unified database with support and confidence no smaller.

Disadvantage:
o Less number of features in previous system.
o Difficulty to get accurate item set.

Proposed System
In Proposed System, propose an alternative protocol for the secure computation of the union of private subsets. The proposed protocol improves upon that in terms of simplicity and efficiency as well as privacy. In particular, our protocol does not depend on commutative encryption and oblivious transfer (what simplifies it significantly and contributes towards much reduced communication and computational costs). While our solution is still not perfectly secure, it leaks excess information only to a small number (three) of possible coalitions, unlike the protocol of that discloses information also to some single players. In addition, we claim that the excess information that our protocol may leak is less sensitive than the excess information leaked by the protocol.

Advantage:
1) As a rising subject, data mining is playing an increasingly important role in the decision support activity of every walk of life.
2) Get Efficient Item set result based on the customer request.


Attached File(s)
.doc  Secure Mining of Association Rules in Horizontally Distributed Databases.doc (Size: 39.5 KB / Downloads: 21)
 


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