Secure Coding Practices Questions
The principle of secure coding for artificial intelligence is to ensure that AI systems are designed, developed, and implemented with security in mind. This includes incorporating security measures throughout the entire AI development lifecycle, such as secure data handling, secure communication protocols, and robust access controls. Additionally, secure coding for AI involves regularly updating and patching AI systems to address any identified vulnerabilities or weaknesses, as well as conducting thorough security testing and audits to identify and mitigate potential risks.