Random Secure Comparator Selection Based Privacy-Preserving MAXMIN Query Processing in Two-Tiered Sensor Networks

Abstract EN

Privacy-preserving data queries for wireless sensor networks (WSNs) have drawn much attention recently.

This paper proposes a privacy-preserving MAX/MIN query processing approach based on random secure comparator selection in two-tiered sensor network, which is denoted by RSCS-PMQ.

The secret comparison model is built on the basis of the secure comparator which is defined by 0-1 encoding and HMAC.

And the minimal set of highest secure comparators generating algorithm MaxRSC is proposed, which is the key to realize RSCS-PMQ.

In the data collection procedures, the sensor node randomly selects a generated secure comparator of the maximum data into ciphertext which is submitted to the nearby master node.

In the query processing procedures, the master node utilizes the MaxRSC algorithm to determine the corresponding minimal set of candidate ciphertexts containing the query results and returns it to the base station.

And the base station obtains the plaintext query result through decryption.

The theoretical analysis and experimental result indicate that RSCS-PMQ can preserve the privacy of sensor data and query result from master nodes even if they are compromised, and it has a better performance on the network communication cost than the existing approaches.