Examining IoT-Enhanced for Current Developments in Face Image Authentication (FIA) Methods and Their Drawbacks

The quick development of IoT and facial image manipulation (FIM) algorithms, as well as the growth of their user-friendly applications, highlight the pressing need for manipulation detection methods. These techniques need to demonstrate how face photos have been altered and validate their legitimacy. The scientific community has recently taken notice of the phrase “DeepFakes” and methods for detecting them. Take note of the latest methods for identifying watermark-based face image modification as well. The important thing to remember is that every one of these methods has its own set of drawbacks. This study provides a brief introduction to face image modification detection methods, emphasizing both watermarking-based and deep learning-based methods. Afterwards, the paper offers instances that demonstrate their use, stressing a comparison between deep learning. The paper then goes on to give examples of how they might be used, with a focus on comparing deep learning and watermarking-based methods for detecting tampering. Research recommendations and insights into possible future advancements in this fascinating field of study are included in the paper’s conclusion. For scholars actively involved in or interested in this particular field of study, the review in this article is regarded as an essential resource.