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A controlled experimental methodology evaluated the framework\u2019s effectiveness using Damn Vulnerable Web Application (DVWA) and Acunetix databases. The findings reveal that Docker significantly reduces the vulnerability to SQLi attacks by isolating database instances, thereby safeguarding user data and system integrity. While Docker introduces a significant increase in CPU utilisation during high-traffic scenarios, the trade-off ensures enhanced security and reliability for real-world applications. This study highlights Docker\u2019s potential as a practical solution for addressing evolving database security challenges in distributed and cloud environments.<\/jats:p>","DOI":"10.3390\/fi17040156","type":"journal-article","created":{"date-parts":[[2025,4,2]],"date-time":"2025-04-02T04:06:05Z","timestamp":1743566765000},"page":"156","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Database Security and Performance: A Case of SQL Injection Attacks Using Docker-Based Virtualisation and Its Effect on Performance"],"prefix":"10.3390","volume":"17","author":[{"given":"Ade Dotun","family":"Ajasa","sequence":"first","affiliation":[{"name":"School of Computing & Engineering, University of Gloucestershire, The Park, Cheltenham GL50 2RH, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6253-1822","authenticated-orcid":false,"given":"Hassan","family":"Chizari","sequence":"additional","affiliation":[{"name":"School of Computing & Engineering, University of Gloucestershire, The Park, Cheltenham GL50 2RH, UK"}]},{"given":"Abu","family":"Alam","sequence":"additional","affiliation":[{"name":"School of Computing & Engineering, University of Gloucestershire, The Park, Cheltenham GL50 2RH, UK"}]}],"member":"1968","published-online":{"date-parts":[[2025,4,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.eswa.2016.07.023","article-title":"Optimizing security and quality of service in a Real-time database system using Multi-objective genetic algorithm","volume":"64","author":"Zhao","year":"2016","journal-title":"Expert Syst. 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