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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Keika Mori (Deloitte Tohmatsu Cyber LLC, Waseda University), Daiki Ito (Deloitte Tohmatsu Cyber LLC), Takumi Fukunaga (Deloitte Tohmatsu Cyber LLC), Takuya Watanabe (Deloitte Tohmatsu Cyber LLC), Yuta Takata (Deloitte Tohmatsu Cyber LLC), Masaki Kamizono (Deloitte Tohmatsu Cyber LLC), Tatsuya Mori (Waseda University, NICT, RIKEN AIP)

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Jonas Juffinger (Graz University of Technology), Fabian Rauscher (Graz University of Technology), Giuseppe La Manna (Amazon), Daniel Gruss (Graz University of Technology)

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Martin Unterguggenberger (Graz University of Technology), Lukas Lamster (Graz University of Technology), David Schrammel (Graz University of Technology), Martin Schwarzl (Cloudflare, Inc.), Stefan Mangard (Graz University of Technology)

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