A scalable and secure transaction attachment algorithm for DAG-based blockchain
Blockchain, as an innovative distributed ledger technology, has attracted considerable attention in recent years from both academic circles and industry sectors. Its applications span a diverse range of domains, including finance and the Internet of Things (IoT). However, the scalability of blockcha...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Pompeu Fabra |
| Repositorio: | Repositorio Digital de la UPF |
| OAI Identifier: | oai:repositori.upf.edu:10230/71753 |
| Acceso en línea: | http://hdl.handle.net/10230/71753 http://dx.doi.org/10.1109/JIOT.2024.3521680 |
| Access Level: | acceso abierto |
| Palabra clave: | Distributed ledger system Internet of Things (IoT) IOTA blockchain network Network modeling |
| Sumario: | Blockchain, as an innovative distributed ledger technology, has attracted considerable attention in recent years from both academic circles and industry sectors. Its applications span a diverse range of domains, including finance and the Internet of Things (IoT). However, the scalability of blockchain technology is still a critical limitation with the increasing volume of data. To address this limitation, a directed acyclic graph (DAG) data structure has been proposed to improve scalability by supporting asynchronous process of transactions. IOTA is a well-known DAG-based blockchain that theoretically offers faster confirmation speeds with an increasing number of transactions. However, in practice, IOTA still faces the challenge of balancing scalability and security. In this article, we propose a scalable and secure transaction attachment algorithm for the DAG-based blockchain IOTA. We determine two critical parameters through our experimental analysis: one for calculating the selection probability and the other for setting the threshold for abnormal transactions. First, we calculate the selection probability of unconfirmed transactions. Then, we select abnormal transactions whose selection probability falls below the predefined threshold to maintain the security. Finally, new transactions attach randomly to former transactions with a time computational complexity O(n) , ensuring the scalability. Through experiments comparing the proposed algorithm to the current transaction attaching algorithm, we demonstrate the scalability and security of our proposed algorithm. |
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