Enhanced scalability and privacy for blockchain data using Merklized transactions
Blockchain technology has evolved beyond the use case of electronic cash and is increasingly used to secure, store, and distribute data for many applications. Distributed ledgers such as Bitcoin have the ability to record data of any kind alongside the transfer of monetary value. This property can b...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-01-01
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| Series: | Frontiers in Blockchain |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fbloc.2023.1222614/full |
| _version_ | 1827386853130502144 |
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| author | Jack Davies Jack Davies |
| author_facet | Jack Davies Jack Davies |
| author_sort | Jack Davies |
| collection | DOAJ |
| description | Blockchain technology has evolved beyond the use case of electronic cash and is increasingly used to secure, store, and distribute data for many applications. Distributed ledgers such as Bitcoin have the ability to record data of any kind alongside the transfer of monetary value. This property can be used to provide a source of immutable, tamper-evident data for a wide variety applications spanning from the supply chain to distributed social media. However, this paradigm also presents new challenges regarding the scalability of data storage protocols, such that the data can be efficiently accessed by a large number of users, in addition to maintaining privacy for data stored on the blockchain. Here, we present a new mechanism for constructing blockchain transactions using Merkle trees comprised of transaction fields. Our construction allows for transaction data to be verified field-wise using Merkle proofs. We show how the technique can be implemented either at the system level or as a second layer protocol that does not require changes to the underlying blockchain. This technique allows users to efficiently verify blockchain data by separately checking targeted individual data items stored in transactions. Furthermore, we outline how our protocol can afford users improved privacy in a blockchain context by enabling network-wide data redaction. This feature of our design can be used by blockchain nodes to facilitate easier compliance with regulations such as GDPR and the right to be forgotten. |
| first_indexed | 2024-03-08T15:52:38Z |
| format | Article |
| id | doaj.art-553bef888c2942b091a14abdda113745 |
| institution | Directory Open Access Journal |
| issn | 2624-7852 |
| language | English |
| last_indexed | 2024-03-08T15:52:38Z |
| publishDate | 2024-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Blockchain |
| spelling | doaj.art-553bef888c2942b091a14abdda1137452024-01-09T04:18:12ZengFrontiers Media S.A.Frontiers in Blockchain2624-78522024-01-01610.3389/fbloc.2023.12226141222614Enhanced scalability and privacy for blockchain data using Merklized transactionsJack Davies0Jack Davies1Research and Development, nChain, London, United KingdomCentre for Networks and Collective Behaviour, University of Bath, Bath, United KingdomBlockchain technology has evolved beyond the use case of electronic cash and is increasingly used to secure, store, and distribute data for many applications. Distributed ledgers such as Bitcoin have the ability to record data of any kind alongside the transfer of monetary value. This property can be used to provide a source of immutable, tamper-evident data for a wide variety applications spanning from the supply chain to distributed social media. However, this paradigm also presents new challenges regarding the scalability of data storage protocols, such that the data can be efficiently accessed by a large number of users, in addition to maintaining privacy for data stored on the blockchain. Here, we present a new mechanism for constructing blockchain transactions using Merkle trees comprised of transaction fields. Our construction allows for transaction data to be verified field-wise using Merkle proofs. We show how the technique can be implemented either at the system level or as a second layer protocol that does not require changes to the underlying blockchain. This technique allows users to efficiently verify blockchain data by separately checking targeted individual data items stored in transactions. Furthermore, we outline how our protocol can afford users improved privacy in a blockchain context by enabling network-wide data redaction. This feature of our design can be used by blockchain nodes to facilitate easier compliance with regulations such as GDPR and the right to be forgotten.https://www.frontiersin.org/articles/10.3389/fbloc.2023.1222614/fullblockchainscalabilityprivacyefficiencynetworksdata |
| spellingShingle | Jack Davies Jack Davies Enhanced scalability and privacy for blockchain data using Merklized transactions Frontiers in Blockchain blockchain scalability privacy efficiency networks data |
| title | Enhanced scalability and privacy for blockchain data using Merklized transactions |
| title_full | Enhanced scalability and privacy for blockchain data using Merklized transactions |
| title_fullStr | Enhanced scalability and privacy for blockchain data using Merklized transactions |
| title_full_unstemmed | Enhanced scalability and privacy for blockchain data using Merklized transactions |
| title_short | Enhanced scalability and privacy for blockchain data using Merklized transactions |
| title_sort | enhanced scalability and privacy for blockchain data using merklized transactions |
| topic | blockchain scalability privacy efficiency networks data |
| url | https://www.frontiersin.org/articles/10.3389/fbloc.2023.1222614/full |
| work_keys_str_mv | AT jackdavies enhancedscalabilityandprivacyforblockchaindatausingmerklizedtransactions AT jackdavies enhancedscalabilityandprivacyforblockchaindatausingmerklizedtransactions |