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Hilbert-Curve Based Data Aggregation Scheme to Enforce Data Privacy and Data Integrity for Wireless Sensor Networks
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Data aggregation techniques have been proposed for wireless sensor networks (WSNs) to address the problems presented by the limited resources of sensor nodes. The provision of efficient data aggregation to preserve data privacy is a challenging issue in WSNs. Some existing data aggregation methods for preserving data privacy are CPDA, SMART, the Twin-Key based method, and GP2S. These methods, however, have two limitations. First, the communication cost for network construction is considerably high. Second, they do not support data integrity. There are two methods for supporting data integrity, iCPDA and iPDA. But they have high communication cost due to additional integrity checking messages. To resolve this problem, we propose a novel Hilbert-curve based data aggregation scheme that enforces data privacy and data integrity for WSNs. To minimize communication cost, we utilize a tree-based network structure for constructing networks and aggregating data. To preserve data privacy, we make use of both a seed exchange algorithm and Hilbert-curve based data encryption. To support data integrity, we use an integrity checking algorithm based on the PIR technique by directly communicating between parent and child nodes. Finally, through a performance analysis, we show that our scheme outperforms the existing methods in terms of both energy efficiency and privacy preservation.
Hilbert-Curve; Data Aggregation; Data Privacy; Data Integrity; Wireless Sensor Networks
Journal Title
International journal of distributed sensor networks
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7. KISTI 연구성과 > 학술지 발표논문
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