In recent years, videos have been susceptible not only to any edition but also to a variety of forgeries. One of the most popular video forgeries is frame deletion, in which a group of frames is removed to hide specific actions from the human eye. When frame deletion occurs, videos selected as evidence lose their evidentiary value. This highlights the necessity of automation, especially for analyzing large volumes of videos. Thus, we measure the performance of two deep learning approaches for frame deletion detection. Both of them use Convolutional Neural Networks (CNN): The first one, a supervised 3DCNN model and, the second one, is an unsupervised model compound of VGG-16 and Resnet-50. We evaluated them using 10-fold cross-validation in the following datasets: UCF-101, VIFFD and DTD (Driving Test Dataset), which is our contribution to the data community. To the best of our knowledge, no comparison of both approaches using 10-fold cross-validation has been found in the literature before. Afterward, we analyze the results and make recommendations for future work in this area.

Blockchain has become an important alternative in plenty of industries due to its features such as traceability, transparency and data integrity. Blockchain is not only present in the management of structured data-like names, timestamps, addresses and so on, but also in the management of unstructured data such as videos or images. In the present work, we focus on videos because nowadays, they are potentially exposed to be modified or altered from plenty of sources and platforms. However, we found that there are hardly any surveys or systematic literature reviews containing applications of both blockchain and integrity of videos. Thus, in this survey, we state a literature review for primary articles about the use of blockchain for video integrity to update and provide a better comprehension about this topic. As results, we encountered Ethereum and internet of vehicles as the largest underlying blockchain and field of application, respectively. At the end, we explain our findings about blockchains for video integrity and why it is an emerging topic.