There exist Adversarial Examples (AEs) that intentionally misclassified images of neural networks to a different class. We propose a method of attack by AEs that uses lasers to facilitate control of misclassification. A previous work has shown that road signs can be misclassified by irradiating them with lasers. We focus on the effective attack in the situations that the attacker can prepare the road signs. Namely, in our attack, the attacker prepares the road signs made by using AEs with missing perturbation, and makes misclassified by using laser irradiation in effective. In this paper, we present principle and method for misclassifying the road signs made by the AEs with missing perturbation by using laser irradiation. In addition, we demonstrate the effectiveness of the proposed method by experiments.

In this paper, we propose a new channel model of optical satellite-to-ground link by analyzing the results of optical transmission experiments between ground station and the Optical Inter-orbit Communications Engineering Test Satellite (OICETS). This will be a practical model on high-capacity optical satellite-to-ground links. In addition, we propose an efficient channel coding scheme using low-density generator matrix (LDGM) codes as a long erasure code over the proposed channel model. Simulation results clarify the required coding rate and the interleaver size for this channel on bare 1 Mbps transmission. The basic idea of the proposed model and the coding system are suitable for higher-speed optical links.