Enabling Data Marketplaces with Multi-Party Computation (MPC)

An Exploratory Study investigating the Implication of the Maturation of Multi-Party Computation (MPC) technology to the Architecture and the Threat Landscape of the Data Marketplaces

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Abstract

The emergence of the Data Marketplaces is the latest iteration in the phenomenon of data-driven transformation of the world. Data marketplaces have emerged as a new form of data-driven business models which enable trading of data between the data owners/providers and data consumers by providing the necessary technological and non-technological infrastructure. These features present an alternative to the cumbersome logistics currently involved in searching, buying and selling data; thus, simplify the data supply chains between the data-driven business entities. However, they suffer to take off into mainstream success because of a myriad of reasons. Of all the reasons, 2 of them are focused in this thesis. Firstly, the difficulty involved in architecturally enabling a data marketplace platform as the prospective enabling technologies are still immature. Secondly, the uncertainty associated with the commodification of data which comprises of the intellectual property enforcement of data (data ownership), privacy and confidentiality breach (threats), regulatory ignorance (implication of GDPR), reluctance of businesses from participating because of the previous reasons et cetera. This reason is collectively referred as due to the uncertainty around the threat landscape of the data marketplaces. Multi-Party Computation (MPC) technology provide a solution to these problems. Through its capabilities to preserve the confidentiality of data architecturally and thereby securing the interests of the data actors with respect to the uncertainty of the threat landscape around data, MPC can enable safe and secure data sharing between data actors. This characteristic of MPC can help data marketplaces to overcome their challenges and foster their realisation. However, since MPC cannot handle the scale of real-life application, it is not mature enough yet to be incorporated into real-life data marketplaces. An EU funded project called SafeDEED: Safe Data-Enabled Economic Development, proposes to overcome the scalability issue and intends to achieve the maturation of MPC for real-life application. Building upon this forecast, a research was conducted to investigate the implication of the maturation of MPC technology towards the 2 problems faced by data marketplaces, architectural and threat landscape; and the same is documented in this thesis.