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Kaushal A Shah, Devesh C Jinwala, Privacy Preserving, Verifiable and Resilient Data Aggregation in Grid-Based Networks, The Computer Journal, Volume 61, Issue 4, April 2018, Pages 614–628, https://doi.org/10.1093/comjnl/bxy013
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Abstract
The grid-based networks are formed by applications where objects being monitored form a square grid. These applications often demand critical security concerns as the compromise to the data yields adverse effects. There are indeed, several lightweight data aggregation schemes proposed in the literature that aims to minimize the resource overhead, albeit providing the required security attributes. However, as per our observations, the information about the actual deployment of the nodes is not exploited in any of these attempts. In this paper, we exploit the linearity in the deployment of grid-based networks to design an aggregation scheme that eventually entails lesser overhead as compared to the other existing schemes while offering the same level of resilience. As homomorphic encryption is considered to be more secure than obfuscation, we also propose a variant to the proposed scheme using homomorphic encryption. In the scenario with lesser restriction on computation, one can opt for the variant to the proposed scheme. The security analysis using mathematical induction and formal security proofs proves the security of the proposed scheme. To the best of our knowledge, the proposed scheme is the first that achieves privacy preservation, data verification, resilience against node capture and avoidance against collusion attacks in grid-based networks with lesser requirement of key storage and communication cost.