Discrete logarithm based additively homomorphic encryption and secure data aggregation
Information Sciences: an International Journal
Towards a theory for privacy preserving distributed OLAP
Proceedings of the 2012 Joint EDBT/ICDT Workshops
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In this paper, we propose a novel multidimensional privacy-preserving data aggregation scheme for improving security and saving energy consumption in wireless sensor networks (WSNs). The proposed scheme integrates the super-increasing sequence and perturbation techniques into compressed data aggregation, and has the ability to combine more than one aggregated data into one. Compared with the traditional data aggregation schemes, the proposed scheme not only enhances the privacy preservation in data aggregation, but also is more efficient in terms of energy costs due to its unique multidimensional aggregation. Extensive analyses and experiments are given to demonstrate its energy efficiency and practicability. Copyright © 2009 John Wiley & Sons, Ltd. In this paper, we propose a novel multidimensional privacy-preserving data aggregation scheme for improving security and saving energy consumption in wireless sensor networks (WSNs). The proposed scheme integrates the super-increasing sequence and perturbation techniques into compressed data aggregation, and has the ability to combine more than one aggregated data into one. Compared with the traditional data aggregation schemes, the proposed scheme not only enhances the privacy preservation in data aggregation, but also is more efficient in terms of energy costs due to its unique multidimensional aggregation. Extensive analyses and experiments are given to demonstrate its energy efficiency and practicability.