IEEE Access (Jan 2021)

Deposit Decision Model for Data Brokers in Distributed Personal Data Markets Using Blockchain

  • Hyeontaek Oh,
  • Sangdon Park,
  • Jun Kyun Choi,
  • Sungkee Noh

DOI
https://doi.org/10.1109/ACCESS.2021.3104870
Journal volume & issue
Vol. 9
pp. 114715 – 114726

Abstract

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Since personal data becomes a valuable asset for IT industries, the necessity of data ecosystems with personal data trading methodologies is continuously increased, and the concept of data brokers is now widely used in the market. Moreover, utilizing the advantages of blockchain, distributed personal data markets have recently been considered because all participants behave selfishly for their profits in the markets. Since the participants may behave maliciously, it is necessary to prevent such behavior, and one of the considered approaches is putting additional deposits as a penalty into blockchain smart contracts. Since data brokers give various advantages to maintain personal data trading markets, many studies have considered both data brokers and blockchain at the same time. However, those studies have mainly focused on putting deposits into data buyers/sellers but not data brokers. However, since data brokers are also major players in the market, it is necessary to consider deposit decision models for data brokers. Hence, this paper proposes a deposit decision model for data brokers in distributed personal data markets using blockchain. Particularly, this paper proposes a profit model with deposits depending on their behavior for handling contracts and a credit level model that puts fewer deposits for a data broker with a higher credit level to motivate the data brokers’ truthful behavior. With the analysis of the proposed models, this paper shows that the models are feasible to motivate data brokers’ truthful behavior by allocating deposits for not only a large enough penalty but also a fair enough incentive.

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