Graph-based profiling of blockchain oracles

Khaled Almi'ani, Young Choon Lee, Tawfiq Alrawashdeh, Amirmohammad Pasdar

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)
50 Downloads (Pure)


The usage of blockchain technology has been significantly expanded with smart contracts and blockchain oracles. While smart contracts enables to automate the execution of an agreement between untrusted parties, oracles provide smart contracts with data external to a given blockchain, i.e., off-chain data. However, the validity and accuracy of such off-chain data can be questionable that compromises the transparency and immutability chacteristics of blockchain. Despite many studies on the trustworthiness of blockchain oracles, more precisely, off-chain data, their solutions are often 'short-sighted' and dependent on binary decisions. In this paper, we present a novel graph-based profiling method to determine the trustworthiness of blockchain oracles. We construct a graph with oracles as nodes and cumulative average discrepancies of validity and accuracy of data as edge weights. Our profiling method continues to update the graph, edge weights in particular, to distinguish trustworthy oracles. Clearly, this discourages the provision of false and inaccurate data. We have conducted an evaluation study to see the effectiveness of our proposed method, in which we have run the experiments utilizing the Ethereum network. Additionally, we have also calculated the cost of running these experiments. Consequently, our experiment results show that the proposed method achieves around 93% accuracy in identifying the trustworthiness of data sources.

Original languageEnglish
Pages (from-to)24995-25007
Number of pages13
JournalIEEE Access
Publication statusPublished - 2023

Bibliographical note

Copyright the Author(s). Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.


Dive into the research topics of 'Graph-based profiling of blockchain oracles'. Together they form a unique fingerprint.

Cite this