Practical and secure multidimensional query framework in tiered sensor networks

The two-tier architecture consisting of a small number of resource-abundant storage nodes in the upper tier and a large number of sensors in the lower tier could be promising for large-scale sensor networks in terms of resource efficiency, network capacity, network management complexity, etc. In this architecture, each sensor having multiple sensing capabilities periodically forwards the multidimensional sensed data to the storage node, which responds to the queries, such as range query, top-$k$ query, and skyline query. Unfortunately, node compromises pose the great challenge of securing the data collection; the sensed data could be leaked to or could be manipulated by the compromised nodes. Furthermore, chunks of the sensed data could be dropped maliciously, resulting in an incomplete query result, which is the most difficult security breach. Here, we propose a simple yet effective hash tree-based framework, under which data confidentiality, query result authenticity, and query result completeness can be guaranteed simultaneously. In addition, the subtree sampling technique, which could be of independent interest to the other applications, is proposed to efficiently identify the compromised nodes. Last, analytical and extensive simulation studies are conducted to evaluate the performance and security of our methods. Prototype implementation on TelosB mote demonstrates the practicality of our proposed methods.