Concealing party-centric sensitive rules in a centralized data source

  • M. Rajalakshmi
  • T. Purusothaman
Original Article


Developments in leaps and bounds in communication and database technology have made resource sharing easy and simple. Data mining is widely used as a business intelligence tool in order to derive meaningful information from centralized or distributed data sources. Recent advances in data mining algorithms have increased the security risks by revealing the sensitive information contained in a data source. When multiple parties are allowed to mine a centralized data source, sensitive information of one party may become easily accessible by another party which is not secured. This proposed work deals with ways and means to hide sensitive information of various parties thus enabling access to legitimate information while securing the sensitive information of other parties. A new data structure called Reduced Transaction Table (RTT) has been proposed to locate transactions pertaining to the sensitive information without multiple scans of the data source thereby reducing the time complexity. The performance of the proposed method is empirically verified and found that it achieves better performance than the existing one.


Data mining Association rule mining Privacy preserving data mining Sensitive rule Rule hiding Sanitization 


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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  1. 1.Department of Computer Science and Engineering and Information TechnologyCoimbatore Institute of TechnologyCoimbatoreIndia
  2. 2.Department of Computer Science and Engineering and Information TechnologyGovernment College of TechnologyCoimbatoreIndia

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