Video tampering detection is considered one of the major problems in digital media forensics. These tampering methods have observed a significant increase in recent years. The reason behind this is the advancement in different deep learning approaches and the availability of huge amounts of video content on different public domains. However, recent developments in deep learning methods have improved visual content at a greater scale but at the same time, it has given rise to several problems in the sphere of video tampering detection methods. The attackers are involved in creating convincing forgeries which can easily dodge any human eye. The easy access to data on social media platforms has made such data vulnerable to tampering in different ways. In this paper, detailed review of existing technologies related to digital video manipulation has been discussed in a systematic way. A thorough survey of current evaluation methods derived from artificial intelligence is done which can enhance video tampering detection. The goal of this work is to provide an overview of the methods used for verifying video integrity, with a focus on the recently developed methods for detecting deepfake videos.