ABSTRACT
With the advent of Industry 4.0, there are now unprecedented possibilities and challenges to be pursued across numerous domains. However, data privacy preservation is one of the key challenges that needs to be addressed, especially in sensitive domains such as the medical field. This is a critical concern, as the privacy of personal data is of utmost importance, and encryption, watermarking, other data-hiding techniques, and differential privacy are different ways to address this. Most of these techniques need a secure and optimal key that is hard to break by adversaries. Computational intelligence (CI) techniques have rapidly gained popularity as a mainstream research area in artificial intelligence, robotics, and optimization. These intelligent techniques are increasingly used to solve complex optimization problems across various real-world applications. Therefore, this chapter showcases the secure key generation process as a complex optimization process. It also highlights the importance of data privacy, along with challenges, security measures, and the benefits of CI for data privacy preservation, followed by possible future directions.
