Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/33196
Title: | Security and Ownership in User-Defined Data Meshes | Authors: | Pingos, Michalis Christodoulou, Panayiotis Andreou, Andreas S. |
Major Field of Science: | Engineering and Technology | Field Category: | Electrical Engineering - Electronic Engineering - Information Engineering | Keywords: | big data;blockchain;data blueprints;data lakes;data meshes;data products;NFT;smart data processing;systems of deep insight | Issue Date: | 22-Apr-2024 | Source: | Algorithms, 2024, Vol 17, Iss. 4, Article number 169 | Volume: | 17 | Issue: | 4 | Journal: | Algorithms | Abstract: | Data meshes are an approach to data architecture and organization that treats data as a product and focuses on decentralizing data ownership and access. It has recently emerged as a field that presents quite a few challenges related to data ownership, governance, security, monitoring, and observability. To address these challenges, this paper introduces an innovative algorithmic framework leveraging data blueprints to enable the dynamic creation of data meshes and data products in response to user requests, ensuring that stakeholders have access to specific portions of the data mesh as needed. Ownership and governance concerns are addressed through a unique mechanism involving Blockchain and Non-Fungible Tokens (NFTs). This facilitates the secure and transparent transfer of data ownership, with the ability to mint time-based NFTs. By combining these advancements with the fundamental tenets of data meshes, this research offers a comprehensive solution to the challenges surrounding data ownership and governance. It empowers stakeholders to navigate the complexities of data management within a decentralized architecture, ensuring a secure, efficient, and user-centric approach to data utilization. The proposed framework is demonstrated using real-world data from a poultry meat production factory. | URI: | https://hdl.handle.net/20.500.14279/33196 | ISSN: | 19994893 | DOI: | 10.3390/a17040169 | Rights: | Attribution-NonCommercial-NoDerivatives 4.0 International | Type: | Article | Affiliation : | Cyprus University of Technology University of Nicosia |
Publication Type: | Peer Reviewed |
Appears in Collections: | Άρθρα/Articles |
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