Papers › PDFS: Practical Data Feed Service for Smart Contracts

PDFS: Practical Data Feed Service for Smart Contracts

20 Aug 2018arXiv:1808.06641links table onlyarchive 2025-07-28

Juan Guarnizo, Pawel Szalachowski

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Smart contracts are a new paradigm that emerged with the rise of the blockchain technology. They allow untrusting parties to arrange agreements. These agreements are encoded as a programming language code and deployed on a blockchain platform, where all participants execute them and maintain their state. Smart contracts are promising since they are automated and decentralized, thus limiting the involvement of third trusted parties, and can contain monetary transfers. Due to these features, many people believe that smart contracts will revolutionize the way we think of distributed applications, information sharing, financial services, and infrastructures. To release the potential of smart contracts, it is necessary to connect the contracts with the outside world, such that they can understand and use information from other infrastructures. For instance, smart contracts would greatly benefit when they have access to web content. However, there are many challenges associated with realizing such a system, and despite the existence of many proposals, no solution is secure, provides easily-parsable data, introduces small overheads, and is easy to deploy. In this paper we propose PDFS, a practical system for data feeds that combines the advantages of the previous schemes and introduces new functionalities. PDFS extends content providers by including new features for data transparency and consistency validations. This combination provides multiple benefits like content which is easy to parse and efficient authenticity verification without breaking natural trust chains. PDFS keeps content providers auditable, mitigates their malicious activities (like data modification or censorship), and allows them to create a new business model. We show how PDFS is integrated with existing web services, report on a PDFS implementation and present results from conducted case studies and experiments.

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