Method for detection of adversarial attacks on face detection networks

Abstract

The paper is concerned with the problem of detecting adversarial attacks against face detection networks. The paper reviews existing adversarial attacks, as well as defense techniques. A novel defense method is proposed, which provides improved detection quality compared to the base technique. Comparative experiments are conducted on a dataset composed of original and fake images obtained using FGSM and MI_FGSM techniques with various parameters.