## 5 Discussion
### Measures for Enhancing Security in Industrial Applications  
Implementing continuous security monitoring solutions designed to detect and respond to security threats in real-time for industrial applications can also help in mitigating the risks. Security information and event management (SIEM) systems, intrusion detection systems (IDSs), and endpoint detection and response (EDR) solutions are examples of technologies that allow for the detection of suspicious or malicious activity in the database in real-time [45]. Moreover, in industrial settings, destructive measures could involve actions taken on a non-production environment or a replicated database instance, without impacting the live production system. In this scenario, destructive measures could include deliberately exploiting SQL injection vulnerabilities to test the system's resilience, simulate potential attacks, or identify weaknesses in the security defenses, without risking harm to the live environment. The utilization of security tools such as OpenVAS, Nessus, Wireshark, Nmap, and SQLmap is essential for this purpose [46]. These tools aid in detecting potential vulnerabilities in network infrastructure, including misconfigurations exacerbating SQL injection risks. Specifically, SQLmap automates the detection and exploitation of SQL injection flaws within web applications, enabling security teams to assess defenses effectively and prioritize remediation efforts [47].  
Regarding addressing the challenges posed by novice programming errors and vulnerabilities introduced by AI-generated code in industrial applications, it is essential to incorporate additional measures tailored to specific requirements, based on standards and industry best practices. Implementing secure coding standards and guidelines, such as those outlined by organizations like Open Web Application Security Project (OWASP) or Computer Emergency Response Team (CERT), can help mitigate common programming errors and vulnerabilities [46]. These practices include input validation, output encoding, proper error handling, and secure authentication mechanisms, which are particularly crucial in industrial settings, where data integrity and system reliability are paramount.  
Establishing robust code review processes--where experienced developers review code written by novice programmers or generated by AI tools--can help identify and address potential security vulnerabilities early in the development lifecycle. Code reviews should focus not only on functionality, but also on security considerations specific to industrial applications, such as ensuring compliance with industry-specific regulations and standards.  
Incorporating security testing into the software development lifecycle of industrial systems, including techniques such as static code analysis, dynamic application security testing (DAST), and penetration testing, can help identify and remediate vulnerabilities in both manually written and AI-generated code. Automated tools like Burp Suite, SonarQube, and Veracode can assist in these efforts, providing specialized features for assessing the security of industrial software systems [48].  
Furthermore, providing ongoing security awareness and training programs for developers in industrial settings is essential. This includes education on secure coding practicesfocused on industrial applications (e.g., Cisco Certified Network Professional), common vulnerabilities specific to industrial environments, and threat modeling techniques adapted to the unique challenges faced by industrial systems. By enhancing the security knowledge and skills of developers, organizations can improve the overall security posture of their industrial systems and reduce the likelihood of introducing vulnerabilities through coding errors or AI-generated code [49].