Securing your ML solution by design
Securing your ML applications is more important than ever due to the growing adoption of AI to provide smart applications. Designing and developing ML systems without keeping security in mind can be costly in terms of exposing the system to hackers, leading to manipulation, data breaches, and non-compliance. Robustness and security play an important role in ensuring an AI system is trustworthy. To build trustworthy ML applications, keeping security in mind is vital to not leave any stones unturned.
Figure 9.8 shows a framework for creating secure ML applications by design. The framework addresses key areas in the ML life cycle, ensuring confidentiality, integrity, and availability within those specific stages. Let's reflect upon each area of the ML life cycle and address the issues of confidentiality, integrity, and availability in each area:
Figure 9.8 – Framework for securing the ML life cycle by design
Let...
