A Language-Agnostic Compression Framework for the Bitcoin Blockchain
| dc.contributor.author | Papanastassiou, Orestes | |
| dc.contributor.supervisor | Thomo, Alex | |
| dc.date.accessioned | 2024-01-18T17:35:31Z | |
| dc.date.available | 2024-01-18T17:35:31Z | |
| dc.date.copyright | 2023 | en_US |
| dc.date.issued | 2024-01-18 | |
| dc.degree.department | Department of Computer Science | en_US |
| dc.degree.level | Master of Science M.Sc. | en_US |
| dc.description.abstract | The surging interdisciplinary interest in Bitcoin within both academic and enterprise realms underscores the need for a versatile framework that can efficiently transform the raw Bitcoin blockchain data into a streamlined format suitable for high-performance data analysis. This research proposes an abstract framework designed to convert this data into a compact, normal form, facilitating its utilization across various programming languages and data analysis tools. Our approach centers on the development of a highly efficient, language-agnostic Application Programming Interface (API). This API is designed to be implementable by any Turing-complete programming language, ensuring broad accessibility and usability. Beyond mere data extraction, our framework extends its capabilities to assemble the Bitcoin user transaction graph, a fundamental resource for downstream analysis, including network analysis, forensics, and pattern detection. To ensure compatibility and ease of integration with an array of programming languages and data analysis software, we export the processed data to the language-agnostic HDF5 file format, recognized and supported by mainstream data analysis tools. This strategic choice empowers researchers and analysts to harness the power of Bitcoin blockchain data without being constrained by software dependencies. Furthermore, to demonstrate the practicality and efficiency of our proposed framework, we present a fully functional CPython implementation as a compelling proof-of-concept. This implementation showcases the feasibility and real-world applicability of our solution, opening doors to a wide range of data-driven investigations and applications within the realm of Bitcoin research. As the interest in Bitcoin continues to evolve and expand, our research offers a comprehensive solution to the challenges of handling and analyzing the vast data included in the blockchain. By providing an accessible, language-agnostic extraction and compression framework, we contribute to the democratization of Bitcoin blockchain data analysis, enabling both novices and experts to uncover valuable insights and drive innovations within this field. | en_US |
| dc.description.scholarlevel | Graduate | en_US |
| dc.identifier.uri | http://hdl.handle.net/1828/15827 | |
| dc.language | English | eng |
| dc.language.iso | en | en_US |
| dc.rights | Available to the World Wide Web | en_US |
| dc.subject | blockchain | en_US |
| dc.subject | bitcoin | en_US |
| dc.subject | data mining | en_US |
| dc.subject | crypto | en_US |
| dc.subject | compression | en_US |
| dc.title | A Language-Agnostic Compression Framework for the Bitcoin Blockchain | en_US |
| dc.type | Thesis | en_US |