Data protection in heterogeneous big data systems

• Published in: Journal of Computer Virology and Hacking Techniques Vol. 19; no. 3; pp. 451 - 458
• Main Authors: Poltavtseva, M. A., Aleksandrova, E. B., Shmatov, V. S., Zegzhda, P. D.
• Format: Journal Article
• Language: English
• Published: Paris Springer Paris 01-09-2023; Springer Nature B.V
• Subjects: Access control; Big Data; Computer Science; Data processing; Data systems; Distributed ledger; Original Paper; Audit; Big data; Distributed ledger; BlockChain; Security; Integrity
• ISSN: 2263-8733; 2263-8733
• DOI: 10.1007/s11416-023-00472-3

Modern Big Data systems are notable for their scale and, often, their distributed organization. A feature of a number of Big Data systems is the use of heterogeneous data processing tools. These are different DBMS and streaming processing tools with different data granularity. The input information may be repeatedly fragmented and re-grouped as it moves between storage locations. In this case, the problems of data integrity, access control and auditing cannot be solved by traditional methods. This paper considers the security of heterogeneous Big Data systems based on distributed ledger technologies and verifiable zero-knowledge operations.