Data Science and Management (Dec 2022)

ACR-MLM: a privacy-preserving framework for anonymous and confidential rewarding in blockchain-based multi-level marketing

  • Saeed Banaeian Far,
  • Azadeh Imani Rad,
  • Maryam Rajabzadeh Asaar

Journal volume & issue
Vol. 5, no. 4
pp. 219 – 231

Abstract

Read online

Network marketing is a trading technique that provides companies with the opportunity to increase sales. With the increasing number of Internet-based purchases, several threats are increasingly observed in this field, such as user privacy violations, company owner (CO) fraud, the changing of sold products’ information, and the scalability of selling networks. This study presents the concept of a blockchain-based market called ACR-MLM that functions based on the multi-level marketing (MLM) model, through which registered users receive anonymous and confidential rewards for their own and their subgroups’ sales. Applying a public blockchain as the ACR-MLM framework’s infrastructure solves existing problems in MLM-based markets, such as CO fraud (against the government or its users), user privacy violations (obtaining their real names or subgroup users), and scalability (when vast numbers of users have been registered). To provide confidentiality and scalability to the ACR-MLM framework, hierarchical identity-based encryption (HIBE) was applied with a functional encryption (FE) scheme. Finally, the security of ACR-MLM is analyzed using the random oracle (RO) model and then evaluated.

Keywords