Innovations in Cyber Security Algorithms for Databases Enhancing Data Retrieval and Management.

  • Published In: Journal of Cybersecurity & Information Management, 2024, v. 13, n. 2. P. 191 1 of 3

  • Database: Applied Science & Technology Source Ultimate 2 of 3

  • Authored By: Gupta, Shyam S.; Kumar, Pankaj; Shrivastava, Rajeev; Jena, Satyabrata; Pandey, Tushar Kumar; Nigam, Ankita 3 of 3

Abstract

The term "Innovations in Cyber Security Algorithms for Databases Enhancing Data Retrieval and Management" refers to a book that studies novel techniques for tackling problems related to digital data. The integration of three complicated methods--DQO, DSS, and RAI--is the major focus of attention in this piece of writing. DQO makes use of machine learning to optimize query processing on the fly to meet fluctuating workloads. This is done to accommodate such workloads. To address issues pertaining to the scale of distributed systems, distributed storage systems (DSS) convey data in an effective manner by utilizing consistent hashing. The RAI algorithm adjusts the index architecture in response to the query patterns to achieve real-time flexibility. In this way, the process of looking for information that is frequently asked about is sped up. The methodology that has been suggested is superior to six different ways that are often used in terms of its adaptability, scalability, and real-time capabilities. This article will give a thorough model for improving data management in computer systems. The objective of this essay is to present the model. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Cybersecurity & Information Management. 2024/04, Vol. 13, Issue 2, p191
  • Document Type:Article
  • Subject Area:Library and Information Science
  • Publication Date:2024
  • ISSN:27697851
  • DOI:10.54216/JCIM.130215
  • Accession Number:179586949
  • Copyright Statement:Copyright of Journal of Cybersecurity & Information Management is the property of American Scientific Publishing Group and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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