## 5 Experimental Results and Discussion
### Discussion  
The next-generation network (NGN) is envisioned to provide ubiquitous services for users with assurance and resilience guarantees. In this work, a video data-sharing platform based on IoV scenarios is introduced as a case study to explore the new frontier of NGN from a practical point of view. The proposed D2 WaVe promises to enable a secure and open-access data service framework by integrating digital watermarking and blockchain technology with the current IoV network architecture. The experimental results are merely a preliminary study on a proof-of-concept implementation. However, our current D2 WaVe prototype, especially for the FIAE-GAN-based digital watermarking model and blockchain-based authentication framework, remains nascent.  
Using pre-trained deep learning models to create fake content that looks realistic to the human eye, deepfaked video, audio, or photos has raised serious concerns about public safety. There are many research efforts on deepfake attacks on digital content, such as a deepfake detector that combines robust and fragile speech watermarking schemes [49] and using Electrical Network Frequency (ENF) fingerprints embedded in images to identify deepfake attacks [36]. However, the proposed FIAE-GAN model cannot address deepfake attacks on watermarked images due to the lack of available technology. This needs more investigation on diverse adversary attacks on the proposed digital watermarking method, such as deepfake attacks on watermarked images, adversarial example attacks and backdoor attacks on FIAE-GAN model.  
The proposed D2 WaVe framework aims to address authenticity and auditability during video data storing and sharing stages for non-real-time scenarios like traffic optimization and accidents analysis. Thus, experimental cases are conducted at a simulated edge computing environment (desktop) to evaluate latency incurred by FIAE-GAN digital watermarking. However, there are many challenges when directly applying the FIAE-GAN model in real-time platforms like ECU and smart cameras. One challenge is implementing a lightweight FIAE-GAN model that can be affordable on edge devices that have limited computation and memory to execute watermark embedding and extraction. In addition, H.264 has been adopted by video and image data in IoV networks to reduce communication overhead and achieve real-time decision tasks [50]. However, the current version of the FIAE-GAN model cannot ensure robustness and invisibility as embedding watermarks into H.264 and other compression videos used in practical situations. This is another challenge of adopting the FIAE-GAN model in real-world IoV applications: handling different video formats and compression schemes without reducing performance.  
Limited by the selection of devices and software, the current version of the prototype only verifies the feasibility of the proposed D2 WaVe framework under a small-scale simulation network. Thus, scalability issues incurred by blockchain technology, such aslong transaction commitment latency and low throughput due to underlying consensus protocols, need to be considered. Future endeavors could integrate lightweight blockchain to enhance efficiency and scalability for large-scale IoV networks [51].