ADVERSARIAL ATTACKS ON FACIAL RECOGNITION SYSTEMS

Abstract: In machine learning, neural networks have shown to achieve state-of-the-art performance within image classifi€cation problems. ‘Though, recent work has brought up a threat to these high performing networks in the form of adversarial att‹acks. ‘These a‹ttacks fool the networks by applying small and hardly perceivable perturbations and questions the reliability of neural networks. ‘This paper will analyze and compare the behavior of adversarial a‹ttacks where reliability and safety is crucial, within facial recognition systems.