Homomorphic Encryption for AI-Based Applications: Challenges and Opportunities

Homomorphic encryption is a technique that allows computations with encrypted data without revealing the data or requiring decryption. This technique has many potential applications in artificial intelligence (AI), where privacy and security are critical. However, implementing homomorphic encryption for AI also presents many challenges and opportunities from a software engineering perspective. In this paper, we provide a comprehensive overview of the current state of the art in homomorphic encryption for AI-based applications and discuss some important software engineering aspects of implementing homomorphic encryption solutions for AI scenarios. We review recent research challenges in applying homomorphic encryption to AI-based applications and discuss their software engineering aspects. We also compare different homomorphic encryption algorithms and libraries in terms of their security, performance, usability, interoperability, functionality, and scalability. Finally, we highlight some open challenges and future directions for research and development in this area.