Subscription-Based Data-Sharing Model Using Blockchain and Data as a Service

In modern times, many individuals, businesses and the Internet of Things (IoT) integrated industries collect huge amounts of meaningful data daily, which may be beneficial for other individuals and businesses as well. By utilizing this data, future trends to make the right decisions on the bases of facts and figures are analyzed efficiently. In addition to that, many new ways are paved for researchers to utilize this data in their upcoming research. However, due to some major issues like security, privacy and access control of data, data owners avoid sharing data among themselves. Another main problem is the selfish behavior of data owners. Businesses also act selfishly and invest huge amounts of money to collect and maintain the data for their benefits. Therefore, data owners are hesitant to share their data with others without the availability of a fair profit and secure data-sharing platform. Moreover, consumers are not much motivated to buy data from Data Providers (DPs) due to its bad quality and inconsistency. The data provided by data owners is mostly incomplete, outdated, heterogeneous and costly. In this paper, a subscription-based data-sharing model is proposed by leveraging the blockchain technology and Data as a Service (DaaS) concept. In this model, users subscribe to a DP for a specific period to get access to the data and pay according to the subscription plan. The DP keeps receiving revenue recurrently for a long-time, which has a huge profit margin in comparison with selling data at once. Furthermore, two major pricing models, Flat Rate Pricing (FRP) and Usage-Based Pricing (UBP), are discussed to set standards for data owners to monetize their data, and a new hybrid pricing model is also proposed. Blockchain technology is utilized in the proposed model to make it secure, transparent and immutable. To investigate the performance of the proposed model, a private blockchain network is deployed using a web interface provided by MultiChain blockchain. The simulation results demonstrate that the proposed model is feasible and efficient. The theoretical discussion proves that the proposed model is beneficial for both data owners and data consumers and has a good scope in the future for data management and trading processes.

[1]  Tao Zhou,et al.  A Blockchain-Based Location Privacy Protection Incentive Mechanism in Crowd Sensing Networks , 2018, Sensors.

[2]  Satoshi Nakamoto.  Bitcoin : A Peer-to-Peer Electronic Cash System , 2009 .

[3]  Ke Xiao,et al.  A Blockchain Based Privacy-Preserving Incentive Mechanism in Crowdsensing Applications , 2018, IEEE Access.

[4]  Honggang Zhang,et al.  Incentive mechanism for proximity-based Mobile Crowd Service systems , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[5]  Aiqing Zhang,et al.  Towards Secure and Privacy-Preserving Data Sharing in e-Health Systems via Consortium Blockchain , 2018, Journal of Medical Systems.

[6]  Nadeem Javaid,et al.  A Secure Data Sharing Platform Using Blockchain and Interplanetary File System , 2019, Sustainability.

[7]  Kai Fan,et al.  MedBlock: Efficient and Secure Medical Data Sharing Via Blockchain , 2018, Journal of Medical Systems.

[8]  Xuliang Duan,et al.  A Pricing Model for Big Personal Data , 2016 .

[9]  Mohsen Guizani,et al.  MeDShare: Trust-Less Medical Data Sharing Among Cloud Service Providers via Blockchain , 2017, IEEE Access.

[10]  Nadeem Javaid,et al.  Secure Service Provisioning Scheme for Lightweight IoT Devices With a Fair Payment System and an Incentive Mechanism Based on Blockchain , 2020, IEEE Access.

[11]  Sai Ji,et al.  Incentive Mechanism of Data Storage Based on Blockchain for Wireless Sensor Networks , 2018, Mob. Inf. Syst..

[12]  Yang Gao,et al.  An incentive mechanism with privacy protection in mobile crowdsourcing systems , 2016, Comput. Networks.

[13]  Nadeem Javaid,et al.  A Blockchain Model for Fair Data Sharing in Deregulated Smart Grids , 2019, 2019 IEEE Global Communications Conference (GLOBECOM).

[14]  Yaling Zhang,et al.  A Blockchain-Based Framework for Data Sharing With Fine-Grained Access Control in Decentralized Storage Systems , 2018, IEEE Access.

[15]  Shengli Xie,et al.  Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks , 2019, IEEE Internet of Things Journal.

[16]  Lidong Wang,et al.  Heterogeneous Data and Big Data Analytics , 2017 .

[17]  Chao Lu,et al.  Privacy-Preserving Auction for Big Data Trading Using Homomorphic Encryption , 2020, IEEE Transactions on Network Science and Engineering.

[18]  Hong-Ning Dai,et al.  An Overview on Smart Contracts: Challenges, Advances and Platforms , 2019, Future Gener. Comput. Syst..

[19]  Florian Stahl,et al.  Pricing Approaches for Data Markets , 2012, BIRTE.

[20]  Xiuzhen Cheng,et al.  A Blockchain Based Truthful Incentive Mechanism for Distributed P2P Applications , 2018, IEEE Access.

[21]  Julita Vassileva,et al.  Blockchain-Based Research Data Sharing Framework for Incentivizing the Data Owners , 2018, ICBC.

[22]  Nadeem Javaid,et al.  Cloud Based Secure Service Providing for IoTs Using Blockchain , 2019, 2019 IEEE Global Communications Conference (GLOBECOM).

[23]  Mohsen Guizani,et al.  BPDS: A Blockchain Based Privacy-Preserving Data Sharing for Electronic Medical Records , 2018, 2018 IEEE Global Communications Conference (GLOBECOM).

[24]  Stefano Bistarelli,et al.  End-to-End Voting with Non-Permissioned and Permissioned Ledgers , 2019, Journal of Grid Computing.

[25]  Qi Xia,et al.  BBDS: Blockchain-Based Data Sharing for Electronic Medical Records in Cloud Environments , 2017, Inf..

[26]  Jeffrey K. MacKie-Mason,et al.  Pricing the Internet , 1995 .

[27]  Xiaohong Zhang,et al.  Data Security Sharing and Storage Based on a Consortium Blockchain in a Vehicular Ad-hoc Network , 2019, IEEE Access.

[28]  Shilin Wen,et al.  Blockchain-Enabled Data Collection and Sharing for Industrial IoT With Deep Reinforcement Learning , 2019, IEEE Transactions on Industrial Informatics.