Privacy Preserving Data Mining as Proof of Useful Work: Exploring an AI/Blockchain Design

【Author】 Turesson, Hjalmar K.; Kim, Henry; Laskowski, Marek; Roatis, Alexandra

【Source】JOURNAL OF DATABASE MANAGEMENT

【影响因子】2.656

【Abstract】Blockchains rely on a consensus among participants to achieve decentralization and security. However, reaching consensus in an online, digital world where identities are not tied to physical users is a challenging problem. Proof-of-work provides a solution by linking representation to a valuable, physical resource. While this has worked well, it uses a tremendous amount of specialized hardware and energy, with no utility beyond blockchain security. Here, the authors propose an alternative consensus scheme that directs the computational resources to the optimization of machine learning (ML) models - a task with more general utility. This is achieved by a hybrid consensus scheme relying on three parties: data providers, miners, and a committee. The data provider makes data available and provides payment in return for the best model, miners compete about the payment and access to the committee by producing ML optimized models, and the committee controls the ML competition.

【Keywords】Blockchain Mining; Distributed Systems; Machine Intelligence; Predictive Analytics; Proof-of-Useful-Work

【发表时间】2021 JAN-MAR

【收录时间】2022-01-02

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