A New Architecture for Data Analysis on Blockchain Without Data Replication
Miguel Rodrigues Baptista (),
Miguel Mira da Silva (),
Paulo Rupino da Cunha () and
Cláudia Antunes ()
Additional contact information
Miguel Rodrigues Baptista: Instituto Superior Técnico & INOV
Miguel Mira da Silva: Instituto Superior Técnico & INOV
Paulo Rupino da Cunha: CISUC, DEI
Cláudia Antunes: Instituto Superior Técnico
A chapter in Advances in Information Systems Development, 2024, pp 23-40 from Springer
Abstract:
Abstract The interest on the discovery of information hidden in large amounts of data exploded in the last decade, bringing to light the need of efficient and effective tools to access all sources and kinds of data. On the other hand, the need to secure and share valuable data led to the development of new technologies, like blockchain, that warrant data integrity and transparency. Combining both is a natural demand, but several issues become clear, such as the lack of access efficiency and the need of data replication in common solutions. Indeed, the unique existing approach is by emulating queries, mostly through Smart Contracts, and applying traditional machine learning algorithms over the resulting data, stored externally for allowing multiple accesses. In this paper, we performed a systematic literature review that provides the above conclusions. Later, we discuss a new system architecture for the analysis of data stored in a blockchain, exploring the scalability and high-performance of data access in distributed file systems and the fast and up-to-date predictions of a streaming analysis approach.
Keywords: Blockchain; Information system security; Data analysis; Incremental machine learning; Distributed file system (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-031-57189-3_2
Ordering information: This item can be ordered from
http://www.springer.com/9783031571893
DOI: 10.1007/978-3-031-57189-3_2
Access Statistics for this chapter
More chapters in Lecture Notes in Information Systems and Organization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().