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Journal of Engineering
Volume 2014, Article ID 470416, 10 pages
Research Article

Analysis and Evaluation of Schemes for Secure Sum in Collaborative Frequent Itemset Mining across Horizontally Partitioned Data

Computer Engineering Department, Sardar Vallabhbhai National Institute of Technology, Surat 395007, India

Received 25 August 2014; Accepted 10 November 2014; Published 30 November 2014

Academic Editor: Jiun-Wei Horng

Copyright © 2014 Nirali R. Nanavati et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Privacy preservation while undertaking collaborative distributed frequent itemset mining (PPDFIM) is an important research direction. The current state of the art for privacy preservation in distributed frequent itemset mining for secure sum in a horizontally partitioned data model comprises primarily public key based homomorphic schemes which are expensive in terms of the communication and computation cost. The nonpublic key based existing state-of-the-art scheme by Clifton et al. used for secure sum in PPDFIM is efficient but prone to security attacks. In this paper, we propose Shamir’s secret sharing based approaches and a symmetric key based scheme to calculate the secure sum in PPDFIM. These schemes are information theoretically secure under the standard assumptions. We further give a detailed theoretical and empirical evaluation of our proposed schemes for PPDFIM using a real market basket dataset. Our experimental analysis also shows that our schemes perform better in terms of the execution cost compared to the public key based scheme for secure sum in PPDFIM.