Name
Abstract | ||
|---|---|---|
Nowadays, the IoT ecosystem is evolving rapidly, with multiple heterogeneous sources producing high volumes of data and processes transforming this data into meaningful or “smart” information. These volumes of data, including IoT data, need to be stored in repositories that can host raw, unprocessed, relational and non-relational types of data, such as Data Lakes. Due to the weakness of metadata management, security & access control is one of the main challenges of Big Data storage architectures as Data Lakes can be replaced without oversight of the contents. Recently, the Blockchain technology has been introduced as an effective solution to build trust between different entities, where trust is either nonexistent or unproven, and to address security and privacy concerns. In this paper we introduce DLMetaChain, an extended Data Lake metadata mechanism that consists of data from heterogeneous data sources which interact with IoT data. The extended mechanism mainly focuses on developing an architecture to ensure that the data in the Data Lake is not modified or altered by taking into advantage the capabilities of the Blockchain. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/IISA56318.2022.9904404 | 2022 13th International Conference on Information, Intelligence, Systems & Applications (IISA) |
Keywords | DocType | ISBN |
Internet of Things,Smart Data Processing,Data Lakes,Heterogeneous Data Sources,Metadata Mechanism,Data Blueprint,Blockchain,Smart Contracts | Conference | 978-1-6654-6391-1 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Michalis Pingos | 1 | 0 | 0.34 |
| Panayiotis Christodoulou | 2 | 0 | 0.34 |
| Andreas S. Andreou | 3 | 216 | 36.65 |