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Abstract The field surveillance of fuel dispensers The field surveillance of fuel dispensers is an activity of Legal Metrology that checks these measuring instruments' correct behavior. However, it constitutes a complex challenge because malicious entities can tamper with fuel dispensers to get undue economic advantages. This paper proposes a distributed and decentralized solution. We use IoT-based vehicle simple meters to estimate the fuel amount in refilling events. Although these estimates can be inaccurate, we explore properties of the Law of the Large Numbers to evaluate the fuel dispenser's accuracy. We also use blockchains to avoid collusion attacks and provide a truly distributed and decentralized surveillance solution that implements statistical surveillance analysis as smart contracts. We develop a case study based on the vehicular fleet and fuel dispensers in São Paulo, Brazil. We perform our experiment using the Hyperledger Fabric platform with Byzantine fault-tolerant consensus. In a hypothetical scenario where vehicular meters present error rates below 5%, and each vehicle refuels more than ten times on average, we can identify tampered fuel dispensers with sensitivity and specificity over 95%. We also demonstrate that our blockchain deployment can support a workload of 600 concurrent clients with a throughput higher than 350 tps and latency lower than 1 s. These results attest to our framework suitability in terms of accuracy and performance. They provide promising perspectives on using our idea in the metrological surveillance of other measuring instruments. rveillance of other measuring instruments.
Author Wilson S. Melo Jr + , Luis V. G. Tarelho + , Bruno A. Rodrigues Filho + , Alysson Bessani + , Luiz F. R. C. Carmo +
Journal Journal of Network and Computer Applications  +
Key Melo21fuelblockchain  +
Month feb  +
NumPubDate 2,021.02  +
ResearchLine Fault and Intrusion Tolerance in Open Distributed Systems (FIT) +
Title Field surveillance of fuel dispensers using IoT-based metering and blockchains  +
Type article  +
Url  +
Volume 175  +
Year 2021  +
Categories Publication  +
Modification dateThis property is a special property in this wiki. 29 September 2021 16:26:07  +
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