Efficient Privacy Preserving Distributed Association Rule Mining Protocol Based on Random Number

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 243)


The rapid advances in recent years in the field of data mining have lead to concern about privacy. The main aim of privacy preserving data mining is to find the global mining results without leaking individual information. For satisfying the privacy constraints, algorithms based on cryptography techniques, data perturbation, information hiding, k-anonymization, secure scalar product, and secret sharing technique are used. In this paper, we propose secure protocol for association rule mining using vector dot product over vertically distributed data among multiple parties. Our method is secure, more efficient and requires less communication cost.


Privacy Association rule mining Secure multi-party computation Vector dot product Privacy preserving data mining 


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Copyright information

© Springer India 2014

Authors and Affiliations

  1. 1.Department of Computer EngineeringPimpri Chinchwad College of EngineeringPuneIndia
  2. 2.Department of Electronics and TelecomK. K. Wagh Institute of Engineering Education and ResearchNashikIndia

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