Preserving privacy in wireless sensor networks using reliable data aggregation

An important topic addressed by the wireless sensor networks community over the last several years is the in-network data aggregation. It is significant as well as a challenging issue to provide reliable data aggregation scheme while preserving data privacy. However, in WSNs, achieving ideal data accuracy is complicated due to collision, heavy network traffic, processing delays and/or several attacks. The problem of gathering accurate integrated data will be further intensified if the environment is adverse. Hence how to attain data privacy and perfect data accuracy are two major challenges for data aggregation in wireless sensor networks. To address this problem, we propose in this paper a new privacy preserving data aggregation scheme. We present REBIVE (REliaBle prIVate data aggrEgation scheme). In REBIVE the data accuracy maintenance and data privacy protection mechanisms work cooperatively. Different from past research, our proposed solution have the following features: providing privacy preservation technique for individual sensor data and aggregated sensor data; maintaining perfect data accuracy for realistic environments; being highly efficient; and being robust to popular attacks launched in WSNs.

在过去几年中，无线传感器网络领域所探讨的一个重要课题是网络内数据聚合。在保护数据隐私的同时提供可靠的数据聚合方案是一个重要且具有挑战性的问题。然而，在无线传感器网络中，由于冲突、网络流量过大、处理延迟和/或多种攻击，实现理想的数据准确性是复杂的。如果环境恶劣，收集准确的综合数据的问题将进一步加剧。因此，如何实现数据隐私和完美的数据准确性是无线传感器网络中数据聚合面临的两个主要挑战。为了解决这个问题，我们在本文中提出了一种新的隐私保护数据聚合方案。我们提出了REBIVE（可靠的隐私数据聚合方案）。在REBIVE中，数据准确性维护和数据隐私保护机制协同工作。与以往的研究不同，我们提出的解决方案具有以下特点：为单个传感器数据和聚合后的传感器数据提供隐私保护技术；在实际环境中保持完美的数据准确性；高效；对无线传感器网络中常见的攻击具有鲁棒性。