Generative deep learning models are able to create realistic audio and video. This technology has been used to impersonate the faces and voices of individuals. These ``deepfakes'' are being used to spread misinformation, enable scams, perform fraud, and blackmail the innocent. The technology continues to advance and today attackers have the ability to generate deepfakes in real-time. This new capability poses a significant threat to society as attackers begin to exploit the technology in advances social engineering attacks. In this paper, we discuss the implications of this emerging threat, identify the challenges with preventing these attacks and suggest a better direction for researching stronger defences.

翻译：生成式深度学习模型能够创建逼真的音频和视频。该技术已被用于冒充个人的面部和声音。这些"深度伪造"正被用来传播虚假信息、实施诈骗、进行欺诈以及勒索无辜者。随着技术持续进步，如今攻击者已具备实时生成深度伪造的能力。这一新能力对社会构成重大威胁，因为攻击者开始利用该技术实施更高级的社会工程攻击。本文讨论了这一新兴威胁的影响，指出了预防此类攻击面临的挑战，并为研究更强防御措施提出了更好的方向。