| Title | A Threat of Deepfakes as a Weapon on Digital Platform and their Detection Methods |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Khichi, Manish, Kumar Yadav, Rajesh |
| Conference Name | 2021 12th International Conference on Computing Communication and Networking Technologies (ICCCNT) |
| Date Published | jul |
| Keywords | Convolutional Neural Networks(CNNs), Deep Neural Networks(DNNs), DeepFake, Deepfake Detection Challenge(DFDC), Forgery, Generative Adversarial Networks(GANs), History, human factors, machine learning algorithms, Media, Metrics, Neural networks, pubcrawl, Recurrent Neural Networks(RNNs), resilience, Resiliency, Scalability, Voting, Weapons |
| Abstract | Advances in machine learning, deep learning, and Artificial Intelligence(AI) allows people to exchange other people's faces and voices in videos to make it look like what they did or say whatever you want to say. These videos and photos are called "deepfake" and are getting more complicated every day and this has lawmakers worried. This technology uses machine learning technology to provide computers with real data about images, so that we can make forgeries. The creators of Deepfake use artificial intelligence and machine learning algorithms to mimic the work and characteristics of real humans. It differs from counterfeit traditional media because it is difficult to identify. As In the 2020 elections loomed, AI-generated deepfakes were hit the news cycle. DeepFakes threatens facial recognition and online content. This deception can be dangerous, because if used incorrectly, this technique can be abused. Fake video, voice, and audio clips can do enormous damage. This paper examines the algorithms used to generate deepfakes as well as the methods proposed to detect them. We go through the threats, research patterns, and future directions for deepfake technologies in detail. This research provides a detailed description of deep imitation technology and encourages the creation of new and more powerful methods to deal with increasingly severe deep imitation by studying the history of deep imitation. |
| DOI | 10.1109/ICCCNT51525.2021.9580031 |
| Citation Key | khichi_threat_2021 |
A Threat of Deepfakes as a Weapon on Digital Platform and their Detection Methods