  Adversarial attacks have been extensively investigated for machine learning
systems including deep learning in the digital domain. However, the adversarial
attacks on optical neural networks (ONN) have been seldom considered
previously. In this work, we first construct an accurate image classifier with
an ONN using a mesh of interconnected Mach-Zehnder interferometers (MZI). Then
a corresponding adversarial attack scheme is proposed for the first time. The
attacked images are visually very similar to the original ones but the ONN
system becomes malfunctioned and generates wrong classification results in most
time. The results indicate that adversarial attack is also a significant issue
for optical machine learning systems.
