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With the continuous development of artificial intelligence, face recognition is widely used in identity authentication, facial recognition payment, intelligent security and other fields. However, the existence of adversarial samples has great security risks to face recognition. In the face recognition system, the attacker can make the system mistake the identity by adding tiny changes to the face image, thus causing a series of security threats such as system intrusion, illegal access to authority, stolen property, and evasion of legal responsibility. In this paper, we first introduce the basic concept of adversarial attacks, and briefly analyze the typical adversarial sample generation methods in recent years. Then, the adversarial attack security problem of face recognition is discussed. Finally, the research status of face recognition adversarial attacks is analyzed.
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