## 2 Related Works  
Table 1 highlights the software used in related works, especially, the use of Docker images and Docker containers to conduct their implementation, just as this research paper has used the Docker framework for its implementation. The authors of the research paper by [PERSON] et al. [1] highlighted the significant challenges posed by data breaches in 2016. Real-time processing databases, designed to handle constantly changing workloads, are particularly susceptible to these threats. Moreover, both external and internal attacks pose serious risks to databases, often targeting sensitive information, such as commercial secrets, bank details, and personal privacy [1]. The authors of the research paper by [PERSON] et al. [2] further corroborated these findings in their 2017 research. Database Management Systems (DBMSs) are employed to process and store user data. Furthermore, security mechanisms and access controls, such as audit logs, cannot always be relied upon to prevent data breaches. Users, both legitimate and malicious, may abuse their privileges in order to compromise database security. Databases must be capable of promptly detecting breaches and collecting evidence to facilitate investigations [2]. According to the authors [PERSON] and [PERSON] [9], insider threats, particularly those involving the misuse of legitimate account privileges, remain a persistent challenge in database security. Detecting such breaches can be extremely difficult. To address this issue, [PERSON] et al. proposed an adaptive and efficient database intrusion detection algorithm inspired by the Negative Selection algorithm from artificial immune systems and the Danger Theory model [9]. Two recent studies published in 2021 by research authors [PERSON] et al. [10] and [PERSON] et al. [11] emphasise the persistent challenges of data breaches and database security. The increasing reliance on the internet has exacerbated the risks of data leakage and cyber threats. The research paper by [PERSON] et al. [10] analysed data breaches involving personal information between 2018 and 2019, including the 2019 cyberattack on Capital One, which exposed sensitive customer information [9]. Similarly, the research paper by [PERSON] et al. 2021 [11] examined the vulnerabilities of modern business systems to cybersecurity threats. While cybersecurity solutions can mitigate attacks on database storage, human errors, such as the loss or theft of devices containing sensitive data or accidental exposure of security credentials, remain significant contributors to security breaches. Common cyberattacks include cross-site scripting (XSS), privilege escalation, and SQL injection (SQLi). The authors of the research paper by [PERSON] et al. [12] conducted a notable study in 2016, simulating an SQLi attack in a virtual environment using tools such as VirtualBox, VMware Workstation, Wireshark, and GNS3. This research aimed to identify websites vulnerable to SQLi attacks. Subsequently, the authors of the research paper by [PERSON] et al. (2018) advocated for the development of strategies to limit the damage SQLi attacks inflict on user data stored in databases. The research paper by [PERSON] et al. (2018) underscored the importance of acquiring knowledge about software vulnerabilities, given the heavy reliance of academic institutions, the private sector, and government entities on database-related software. This research builds upon this foundation by proposing a method to mitigate SQLi attack damage to user data held in databases ([PERSON] et al., 2018). Hospitals and banks are among the primary victims of SQLi attacks ([PERSON] et al., 2019). Databases accessible via the internet are particularly vulnerable to various types of attacks ([PERSON] et al., 2019). As proposed in the research paper by [PERSON] et al. (2019), an innovative approach involves storing private information within Docker containers. These containers, which are resource-efficient and designed for cloud environments, enhance privacy protection and can be deployed as needed.