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Blockchain-based mechanism for fine-grained authorization in data crowdsourcing
مکانیسم مبتنی بر بلاکچین برای مجوز دانه ریز در جمع آوری داده ها-2019 Data crowdsourcing is a distributed data acquisition method to efficiently collect a sizeable amount
of high-quality data from a large network of contributors who participate in data trading activities.
However, traditional data crowdsourcing platforms are almost invariably based on a centralized architecture,
which tends to give unfair advantages to the platform operator; besides, centralized platforms
are obvious targets for cybersecurity attacks and become a single point of failure. Furthermore, a
centralized approach with stringent security control also suffers from serious scalability issue. For
example, if data owners manage a database with large amounts of valuable data, they have to retrieve
data from their database in accordance with certain access policies and encrypt retrieved data for each
requester; hence they become bottlenecks in the data trading process when the number of requesters
is very large. To address the above issues, we propose a blockchain-based mechanism for fine-grained
authorization in data crowdsourcing (BC-FGA-DCrowd). In the BC-FGA-DCrowd scheme, we use a
public blockchain to implement cryptocurrencies and payment services as incentive schemes for data
trading platform users. With this approach, data owners can employ Ciphertext-Policy Attribute-Based
Encryption (CP-ABE) to pre-process the complex encryption workload, and generate the attribute
private key for data requester to achieve the fine-grained authorization. In this paper, we also prove
that the BC-FGA-DCrowd scheme satisfies the correctness and fairness requirements of data trading,
and can effectively withstand malicious activities of internal users and external DDos and Sybil
attackers. The approach was tested on a private Ethereum network using Ganache with a local host. Keywords: Data crowdsourcing | Blockchain | Smart contracts | Fine-grained authorization | Data trade |
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