SecureAI -iOS: A Privacy-Preserving Framework for Secure Deployment of Generative Intelligence in Mobile Applications

Abstract

The rapid adoption of generative AI in the mobile application poses major privacy and security concerns. This study suggests a SecureAI-iOS privacy-protective framework to develop secure deployment of generative intelligence. The system combines some of the concepts of differential privacy, federated learning, encryption, and machine learning-driven threat detection. Simulated data of experimental evaluation of the simulated mobile AI security data with that data produced an accuracy of 95.67% and explain ability analysis revealed the key aspects of security at risk. The results indicate that the SecureAI-iOS is effective in giving out reliable and safe iOS based generative AI applications.