Generative deep learning algorithms have progressed to a point where it is difficult to tell the difference between what is real and what is fake. In 2018, it was discovered how easy it is to use this technology for unethical and malicious applications, such as the spread of misinformation, impersonation of political leaders, and the defamation of innocent individuals. Since then, these “deepfakes” have advanced significantly. In this article, we explore the creation and detection of deepfakes and provide an in-depth view as to how these architectures work. The purpose of this survey is to provide the reader with a deeper understanding of (1) how deepfakes are created and detected, (2) the current trends and advancements in this domain, (3) the shortcomings of the current defense solutions, and (4) the areas that require further research and attention.

中文翻译：

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Deepfake 的创建和检测

生成式深度学习算法已经发展到难以区分真假的程度。2018 年，人们发现将这项技术用于不道德和恶意应用是多么容易，例如传播错误信息、冒充政治领导人和诽谤无辜个人。从那时起，这些“深度造假”取得了长足的进步。在本文中，我们探讨了 deepfakes 的创建和检测，并深入了解这些架构的工作原理。本次调查的目的是让读者更深入地了解（1）如何创建和检测深度伪造，（2）该领域的当前趋势和进步，（3）当前防御解决方案的缺点，