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http://dx.doi.org/10.3745/KTCCS.2020.9.12.321

Practical Concerns in Enforcing Ethereum Smart Contracts as a Rewarding Platform in Decentralized Learning  

Rahmadika, Sandi (부경대학교 인공지능융합학과)
Firdaus, Muhammad (부경대학교 인공지능융합학과)
Jang, Seolah (부경대학교 인공지능융합학과)
Rhee, Kyung-Hyune (부경대학교 IT융합응용공학과)
Publication Information
KIPS Transactions on Computer and Communication Systems / v.9, no.12, 2020 , pp. 321-332 More about this Journal
Abstract
Decentralized approaches are extensively researched by academia and industry in order to cover up the flaws of existing systems in terms of data privacy. Blockchain and decentralized learning are prominent representatives of a deconcentrated approach. Blockchain is secure by design since the data record is irrevocable, tamper-resistant, consensus-based decision making, and inexpensive of overall transactions. On the other hand, decentralized learning empowers a number of devices collectively in improving a deep learning model without exposing the dataset publicly. To motivate participants to use their resources in building models, a decent and proportional incentive system is a necessity. A centralized incentive mechanism is likely inconvenient to be adopted in decentralized learning since it relies on the middleman that still suffers from bottleneck issues. Therefore, we design an incentive model for decentralized learning applications by leveraging the Ethereum smart contract. The simulation results satisfy the design goals. We also outline the concerns in implementing the presented scheme for sensitive data regarding privacy and data leakage.
Keywords
Blockchain; Data Privacy; Decentralized Learning; Incentive Mechanism; Smart Contract;
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