Database Security and Performance: A Case of SQL Injection Attacks Using Docker-Based Virtualisation and its Effect on Performance

Ajasa, Ade Dotun, Chizari, Hassan ORCID: https://orcid.org/0000-0002-6253-1822 and Alam, Abu S (2025) Database Security and Performance: A Case of SQL Injection Attacks Using Docker-Based Virtualisation and its Effect on Performance. Future Internet. (In Press)

Text 14907 Ajasa, A et al. (2025) Database Security and Performance.pdf - Accepted Version Restricted to Repository staff only Available under License Creative Commons Attribution 4.0. Download (2MB)

Abstract

Modern database systems are critical for storing sensitive information but are increasingly 1 targeted by cyber threats, including SQL injection (SQLi) attacks. This research proposes a robust 2 security framework leveraging Docker-based virtualisation to enhance database security and mitigate 3 the impact of SQLi attacks. A controlled experimental methodology evaluated the framework’s 4 effectiveness using Damn VulnerableWeb Application (DVWA) and Acunetix databases. The findings 5 reveal that Docker significantly reduces the vulnerability to SQLi attacks by isolating database 6 instances, thereby safeguarding user data and system integrity. While Docker introduces a significant 7 increase in CPU utilisation during high-traffic scenarios, the trade-off ensures enhanced security and 8 reliability for real-world applications. This study highlights Docker’s potential as a practical solution 9 for addressing evolving database security challenges in distributed and cloud environments.

Item Type:	Article
Article Type:	Article
Uncontrolled Keywords:	Security; Performance; Virtualisation; Databases
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management > HD61 Risk in industry. Risk management Q Science > QA Mathematics > QA76 Computer software > QA76.9 Other topics > QA76.9.V5 Virtual computer systems Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases
Divisions:	Schools and Research Institutes > School of Business, Computing and Social Sciences
Depositing User:	Kamila Niekoraniec
Date Deposited:	01 Apr 2025 11:14
Last Modified:	01 Apr 2025 11:30
URI:	https://eprints.glos.ac.uk/id/eprint/14907

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