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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EMIRIS: Eavesdropping on Iris Information via Electromagnetic Side Channel

Wenhao Li (Shandong University), Jiahao Wang (Shandong University), Guoming Zhang (Shandong University), Yanni Yang (Shandong University), Riccardo Spolaor (Shandong University), Xiuzhen Cheng (Shandong University), Pengfei Hu (Shandong University)

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type++: Prohibiting Type Confusion with Inline Type Information

Nicolas Badoux (EPFL), Flavio Toffalini (Ruhr-Universität Bochum, EPFL), Yuseok Jeon (UNIST), Mathias Payer (EPFL)

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QMSan: Efficiently Detecting Uninitialized Memory Errors During Fuzzing

Matteo Marini (Sapienza University of Rome), Daniele Cono D'Elia (Sapienza University of Rome), Mathias Payer (EPFL), Leonardo Querzoni (Sapienza University of Rome)

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