The Invisible Shadow: How Security Cameras Leak Private Activities
Jian Gong, Xinyu Zhang, Ju Ren, Yaoxue Zhang
摘要
This paper presents a new privacy threat, the Invisible Infrared Shadow Attack (IRSA), which leverages the inconspicuous infrared (IR) light emitted by indoor security cameras, to reveal in-home human activities behind opaque curtains. The key observation is that the in-home IR light source can project invisible shadows on the window curtains, which can be captured by an attacker outside using an IR-capable camera. The major challenge for IRSA lies in the shadow deformation caused by a variety of environmental factors involving the IR source position and curtain shape, which distorts the body contour. A two-stage attack scheme is proposed to circumvent the challenge. Specifically, a DeShaNet model performs accurate shadow keypoint detection through multi-dimension feature fusion. Then a scene constructor maps the 2D shadow keypoints to 3D human skeletons by iteratively reproducing the on-site shadow projection process in a virtual Unity 3D environment. Through comprehensive evaluation, we show that the proposed attack scheme can be successfully launched to recover 3D skeleton of the victims, even under severe shadow deformation. Finally, we propose potential defense mechanisms against the IRSA.
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