Please use this identifier to cite or link to this item: https://doi.org/10.1145/1525856.1525858
Title: Efficient and provably secure aggregation of encrypted data in wireless sensor networks
Authors: Castelluccia, C.
Chan, A.C.-F. 
Mykletun, E.
Tsudik, G.
Keywords: Authentication
Cryptography
Privacy
Pseudorandom functions
Secure data aggregation
Stream ciphers
Wireless sensor networks
Issue Date: 2009
Source: Castelluccia, C., Chan, A.C.-F., Mykletun, E., Tsudik, G. (2009). Efficient and provably secure aggregation of encrypted data in wireless sensor networks. ACM Transactions on Sensor Networks 5 (3) : 1-36. ScholarBank@NUS Repository. https://doi.org/10.1145/1525856.1525858
Abstract: Wireless sensor networks (WSNs) are composed of tiny devices with limited computation and battery capacities. For such resource-constrained devices, data transmission is a very energy-consuming operation. To maximize WSN lifetime, it is essential to minimize the number of bits sent and received by each device. One natural approach is to aggregate sensor data along the path from sensors to the sink. Aggregation is especially challenging if end-to-end privacy between sensors and the sink (or aggregate integrity) is required. In this article, we propose a simple and provably secure encryption scheme that allows efficient additive aggregation of encrypted data. Only one modular addition is necessary for ciphertext aggregation. The security of the scheme is based on the indistinguishability property of a pseudorandom function (PRF), a standard cryptographic primitive. We show that aggregation based on this scheme can be used to efficiently compute statistical values, such as mean, variance, and standard deviation of sensed data, while achieving significant bandwidth savings. To protect the integrity of the aggregated data, we construct an end-to-end aggregate authentication scheme that is secure against outsider-only attacks, also based on the indistinguishability property of PRFs.
Source Title: ACM Transactions on Sensor Networks
URI: http://scholarbank.nus.edu.sg/handle/10635/39823
ISSN: 15504859
DOI: 10.1145/1525856.1525858
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