On January 15, 2021, the Federal Aviation Administration published the Unmanned Aircraft System Remote Identification rule with the intention of improving airspace security regarding the use of Unmanned Aircraft. According to the rule, UAs in flight must provide the public with information such as their identification, location, and altitude. After the publication of this rule, the IETF DRIP Working Group has been working on the creation of DRIP, a protocol that meets the requirements stipulated in the rule and that guarantees that all the communication involved in the protocol is made trustworthy. This document presents a thesis project in which Hyperledger Fabric has been studied and evaluated as an alternative to replace DRIP's DNS-based registry management. A vast research procedure combined with experiments has aided in creating a novel Blockchain-based Drone ID architecture called HL-DRIP. The designed system proposes not only how blockchain could be integrated into DRIP, but also how the rest of the Remote ID protocol could be designed, and how each of the protocol's components and participants should interact with each other to make the protocol compliant with the rule. HL-DRIP is a blockchain-based system designed to replace DRIP registry management leveraging Hyperledger Fabric and IPFS. HL-DRIP leverages x.509 and DRIP-based certificates to manage participant registration and authentication. A private IPFS network is deployed by the system's smart contract to manage participants' personal data and mitigate well-known blockchain storage issues, allowing the system to be GDPR-compliant. HL-DRIP supports i) participant registration by using certificates and HIP-based unique IDs, ii) lookups of participants' personal data, and iii) permission management. HL-DRIP's main functionality has been prototyped and tested. The results have shown that an average of 783 participants are registered with a throughput of 8.1 transactions per second. Furthermore, an average of 648 IPFS data requests are executed with a throughput of 12.8 transactions per second.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-193082 |
| Date | January 2023 |
| Creators | Basaez Serey, Juan |
| Publisher | Linköpings universitet, Institutionen för datavetenskap, Linköpings University |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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