Yanze Ren (Zhejiang University), Qinhong Jiang (Zhejiang University), Chen Yan (Zhejiang University), Xiaoyu Ji (Zhejiang University), Wenyuan Xu (Zhejiang University)

CCD cameras are critical in professional and scientific applications where high-quality image data are required, and the reliability of the captured images forms the basis for trustworthy computer vision systems. Previous work shows the feasibility of using intentional electromagnetic interference (IEMI) to inject unnoticeable image changes into CCD cameras. In this work, we design an attack of enhanced capability, GhostShot, that can inject any grayscale or colored images into CCD cameras under normal light conditions with IEMI. We conduct a schematic analysis of the causality of the IEMI effect on the shapes, brightness, and colors of the injected images, and achieve effective control of the injected pattern through amplitude-phase modulation. We design an end-to-end attack workflow and successfully validate the attack on 15 commercial CCD cameras. We demonstrate the potential impact of GhostShot on medical diagnosis, fire detection, QR code scanning and object detection and find that the falsified images can successfully mislead computer vision systems and even human eyes.

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Jian Cui (Indiana University), Hanna Kim (KAIST), Eugene Jang (S2W Inc.), Dayeon Yim (S2W Inc.), Kicheol Kim (S2W Inc.), Yongjae Lee (S2W Inc.), Jin-Woo Chung (S2W Inc.), Seungwon Shin (KAIST), Xiaojing Liao (Indiana University)

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