Analysis of Deepfake Attacks and Detection Techniques in Smart City Applications

Deepfake attacks, powered by advanced artificial intelligence, pose a growing threat to the integrity and security of smart city applications. Our study aims to provide valuable insights into countering deepfake threats within the smart city landscape, ensuring the continued trustworthiness of critical systems and data. This paper presents a comprehensive analysis of deepfake attacks and explores state-of-the-art detection techniques that can safeguard the authenticity and reliability of data in smart city environments. We investigated the evolution of deepfake technology and its potential ramifications in the context of smart cities. Additionally, we evaluated various detection algorithms and models, highlighting their strengths and weaknesses. The precision, recall, and F1-score exceeding 95% demonstrate outstanding results, improving the achievements of other works by a substantial margin.