Association Rule Hiding Using Firefly Optimization Algorithm

  • S. SharmilaEmail author
  • S. Vijayarani
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 941)


Privacy preserving data mining is an important research area which protects the private information and reduces the information loss during the data mining process. There are many data mining techniques whereas Association rule mining is one of the data mining technique which finds existing correlations between data items. Privacy Preserving Association Rule Mining is one of the techniques in this field, which aims to hide sensitive association rules. Many different algorithms with particular approaches have been developed to protect the private information. In this paper, a new approach has been introduced using firefly optimization algorithm for hiding the sensitive association rules. To hide the sensitive rules distortion technique was used. Further in this work fitness function was defined to achieve the optimal solution with fewest side effects. The efficiency of proposed algorithm was evaluated with different databases. The results of the execution of the proposed algorithm and existing algorithm tabu search on different databases indicates that firefly algorithm has better performance compared to other algorithm.


Data mining Privacy preserving data mining Association rule hiding Firefly optimization algorithm 


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Computer ScienceBharathiar UniversityCoimbatoreIndia

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