An Efficient Association Rule Hiding Algorithm for Privacy Preserving Data Mining

Journal Title: International Journal on Computer Science and Engineering - Year 2011, Vol 3, Issue 7

Abstract

The security of the large database that contains certain crucial information, it will become a serious issue when sharing data to the network against unauthorized access. Privacy preserving data mining is a new research trend in privacy data for data mining and statistical database. Association analysis is a powerful tool for discovering relationships which are hidden in large database. Association rules hiding algorithms get strong and efficient performance for protecting confidential and crucial data. Data modification and rule hiding is one of the most important approaches for secure data. The objective of the proposed Association rule hiding algorithm for privacy preserving data mining is to hide certain information so that they cannot be discovered through association rule mining algorithm. The main approached of association rule hiding algorithms to hide some generated association rules, by increase or decrease the support or the confidence of the rules. The association rule items whether in Left Hand Side (LHS) or Right Hand Side (RHS) of the generated rule, that cannot be deduced through association rule mining algorithms. The concept of Increase Support of Left Hand Side (ISL) algorithm is decrease the confidence of rule by increase the support value of LHS. It doesn’t work for both side of rule; it works only for modification of LHS. In Decrease Support of Right Hand Side (DSR) algorithm, confidence of the rule decrease by decrease the support value of RHS. It works for the modification of RHS. We proposed a new algorithm solves the problem of them. That can increase and decrease the support of the LHS and RHS item of the rule correspondingly so that more rule hide less number of modification. The efficiency of the proposed algorithm is compared with ISL algorithms and DSR algorithms using real databases, on the basis of number of rules hide, CPU time and the number of modifies entries and got better results.

Authors and Affiliations

Yogendra Kumar Jain , Vinod Kumar Yadav , Geetika S. Panday

Keywords

Related Articles

Analyzing Theoretical Basis and Inconsistencies of Object Oriented Metrics

Metrics help in identifying potential problem areas and finding these problems in the phase they are developed decreases the cost and avoids major ripple effects from these in later development stages. These days, Object...

Effect of Quality Parameters on Energy Efficient Routing Protocols in MANETs

This paper presents a survey on energy efficient routing protocols for wireless Ad-Hoc networks. Survey focus on recent development and modifications in this widely used field. In this paper I present a number of ways of...

Load Balanced Routing using OSPF

Today’s Internet applications are in need of additional bandwidth. The Internet nature changes and its traffic are growing because of new applications. Initially when the file transfers dominated the internet we don’t re...

Recognition of Isolated Handwritten Kannada Numerals based on Decision Fusion Approach

combining classifiers appears as a natural step forward when a critical mass of knowledge of single classifier models has been accumulated. Although there are many unanswered questions about matching classifiers to real-...

FEATURE SELECTION METHODS AND ALGORITHMS

Feature selection is an important topic in data mining, especially for high dimensional datasets. Feature selection (also known as subset selection) is a process commonly used in machine learning, wherein subsets of the...

Download PDF file
  • EP ID EP102878
  • DOI -
  • Views 129
  • Downloads 0

How To Cite

Yogendra Kumar Jain, Vinod Kumar Yadav, Geetika S. Panday (2011). An Efficient Association Rule Hiding Algorithm for Privacy Preserving Data Mining. International Journal on Computer Science and Engineering, 3(7), 2792-2798. https://www.europub.co.uk/articles/-A-102878