Gulshan Kumar, Rahul Saha, Mauro Conti, Tai Hoon Kim
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DEBPIR: enhancing information privacy in decentralized business modeling
Business modelling often involves extensive data collection and analysis, raising concerns about privacy infringement. Integrating Privacy Information Retrieval (PIR) mechanisms within business models is crucial to address privacy concerns, ensure compliance with regulations, safeguard sensitive data, and maintain trust with stakeholders; however, PIR is not included in the existing business models yet. In this paper, we propose the first decentralized business model that uses the PIR. We call our proposed model DEcentralized Business model with PIR (DEBPIR). DEBPIR uses a smart contract for PIR and encryption to share the privacy of classified information. We execute a thorough set of experiments on DEBPIR and evaluate the results based on privacy attainment, latency, and throughput. We also perform a comparative analysis between our proposed DEBPIR and the existing models; we observe that DEBPIR outperforms the existing models and provides \(95\%\) privacy attainment. The latency and throughput of our proposed DEBPIR do not outgrow compared to the existing models. Thus, DEBPIR is an efficient solution for business models.
期刊介绍:
Complex & Intelligent Systems aims to provide a forum for presenting and discussing novel approaches, tools and techniques meant for attaining a cross-fertilization between the broad fields of complex systems, computational simulation, and intelligent analytics and visualization. The transdisciplinary research that the journal focuses on will expand the boundaries of our understanding by investigating the principles and processes that underlie many of the most profound problems facing society today.