Computing Aggregation Function Minimum/Maximum using Homomorphic Encryption Schemes in Wireless Sensor Networks (WSNs)

Data aggregation in wireless sensor networks (WSN) helps eliminate information redundancy and increase the lifetime of the network. When homomorphic encryption is used for data aggregation, end-to-end encryption is achieved and aggregation function like average or minimum/maximum can be computed on the encrypted data. Aggregation functions like minimum/maximum rely on comparison operation. But, it has been shown that any homomorphic encryption is insecure against ciphertext only attacks if they support comparison operation. The order preserving encryption scheme (OPES) has been suggested for WSNs, for secure comparison of encrypted data at the aggregator node in WSNs. But, the computational cost at the sensor nodes in WSNs by using OPES is huge. This paper provides an alternative for OPES when used to calculate aggregation function minimum/maximum. In this paper we briefly describe some homomorphic encryption schemes and show how the sensed data is encrypted by using these homomorphic encryption schemes. we show how aggregation function minimum/maximum can be computed at the aggregator node in WSNs by performing addition operation and not comparison operation on the data encrypted with homomorphic encryption schemes. We also show how our scheme helps eliminate the encryption cost at the sensor node in WSNs.