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06-02-2017, 09:58 PM
Abstract
The architecture of two-tiered sensor networks, where storage nodes serve as an intermediate tier between sensors and a sink for storing data and processing queries, has been widely adopted because of the benefits of power and storage saving for sensors as well as the efficiency of query processing. However, the importance of storage nodes also makes them attractive to attackers. In this paper, we propose SafeQ, a protocol that prevents attackers from gaining information from both sensor collected data and sink issued queries. SafeQ also allows a sink to detect compromised storage nodes when they misbehave. To preserve privacy, SafeQ uses a novel technique to encode both data and queries such that a storage node can correctly process encoded queries over encoded data without knowing their values. To preserve integrity, we propose two schemes—one using Markel hash trees and another using a new data structure called neighborhood chains—to generate integrity verification information so that a sink can use this information to verify whether the result of a query contains exactly the data items that satisfy the query. To improve performance, we propose an optimization technique using Bloom filters to reduce the communication cost between sensors and storage nodes.
The architecture of two-tiered sensor networks, where storage nodes serve as an intermediate tier between sensors and a sink for storing data and processing queries, has been widely adopted because of the benefits of power and storage saving for sensors as well as the efficiency of query processing. However, the importance of storage nodes also makes them attractive to attackers. In this paper, we propose SafeQ, a protocol that prevents attackers from gaining information from both sensor collected data and sink issued queries. SafeQ also allows a sink to detect compromised storage nodes when they misbehave. To preserve privacy, SafeQ uses a novel technique to encode both data and queries such that a storage node can correctly process encoded queries over encoded data without knowing their values. To preserve integrity, we propose two schemes—one using Markel hash trees and another using a new data structure called neighborhood chains—to generate integrity verification information so that a sink can use this information to verify whether the result of a query contains exactly the data items that satisfy the query. To improve performance, we propose an optimization technique using Bloom filters to reduce the communication cost between sensors and storage nodes.