Secure AI for Encrypted Speech and Text Data

Abstract

As the digital landscape expands, the need for secure artificial intelligence (AI) systems capable of processing encrypted speech and text data grows more critical. This abstract explores the challenges and advancements in developing secure AI solutions for encrypted data. The primary focus is on ensuring privacy and confidentiality while maintaining the utility of AI models in analyzing sensitive information. Key aspects include the encryption methods suitable for speech and text data, the integration of AI algorithms capable of operating on encrypted data, and the computational techniques for maintaining efficiency without compromising security. Additionally, the abstract addresses emerging trends and future directions in the field, such as homomorphic encryption, differential privacy, and federated learning, which promise to enhance the robustness and privacy of AI systems in handling encrypted data.