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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Dayong Ye (University of Technology Sydney), Tianqing Zhu (City University of Macau), Congcong Zhu (City University of Macau), Derui Wang (CSIRO’s Data61), Kun Gao (University of Technology Sydney), Zewei Shi (CSIRO’s Data61), Sheng Shen (Torrens University Australia), Wanlei Zhou (City University of Macau), Minhui Xue (CSIRO's Data61)

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Guanlong Wu (Southern University of Science and Technology), Zheng Zhang (ByteDance Inc.), Yao Zhang (ByteDance Inc.), Weili Wang (Southern University of Science and Technolog), Jianyu Niu (Southern University of Science and Technolog), Ye Wu (ByteDance Inc.), Yinqian Zhang (Southern University of Science and Technology (SUSTech))

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Query Privacy in Data Spaces

Shuwen Liu (School of Data Science, The Chinese University of Hong Kong, Shenzhen, China), George C. Polyzos (School of Data Science, The Chinese University of Hong Kong, Shenzhen, China and ExcID P.C., Athens, Greece)

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ASGARD: Protecting On-Device Deep Neural Networks with Virtualization-Based Trusted...

Myungsuk Moon (Yonsei University), Minhee Kim (Yonsei University), Joonkyo Jung (Yonsei University), Dokyung Song (Yonsei University)

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