Abstract
Data aggregators can leverage personal data for the benefit of their users in their role of mediators with enterprises that are willing to target qualified user segments with customized offerings. However, such type of transaction must comply with personal data protection regulation and provide a fair and auditable context for business partners. In this paper, the components of a solution for that problem in the context of a permissioned, private business network are described, along with an implementation using the Quorum enterprise derivative of Ethereum. The results of that design are expressed as a combination of schemas, protocols and smart contracts. The resulting model may serve as a blueprint for experimenting data market mechanisms that exploit the unique value of aggregators in a secure, transparent and auditable framework.
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Note that this would require that the aggregator has a database that is immutable, i.e. an accrual of facts in time, as for example provided by Datomic.
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A better approach may be that of contacting users that have been surveyed and voluntarily disclosed they knew of the proposal via the aggregator.
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Acknowledgements
Project funded by (proyecto financiado por) FEDER/ Ministerio de Ciencia, Innovación y Universidades - Agencia Estatal de Investigación/ Proyecto RTC-2017-6779-7, “Uso de blockchain en una plataforma financiera basada en Big Data, Inteligencia Artificial, machine learning, algoritmos predictivos y herramientas de lenguaje natural para la contratación, gestión e intercambio de activos no financieros.”
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Sicilia, MA. et al. (2020). Qualified Targeting Through Data Aggregators in Permissioned Blockchain Settings: A Model for Auditable Transactions. In: Prieto, J., Pinto, A., Das, A., Ferretti, S. (eds) Blockchain and Applications. BLOCKCHAIN 2020. Advances in Intelligent Systems and Computing, vol 1238. Springer, Cham. https://doi.org/10.1007/978-3-030-52535-4_12
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