DeWiCam

Introduction

Wireless cameras are widely deployed in surveillance systems for security guarding. However, the privacy concerns associated with unauthorized videotaping, are drawing an increasing attention recently. Existing detection methods for unauthorized wireless cameras are either limited by their detection accuracy or requiring dedicated devices. In this work, we propose DeWiCam, a lightweight and effective detection mechanism using smartphones. The basic idea of DeWiCam is to utilize the intrinsic traffic patterns of flows from wireless cameras. Compared with traditional traffic pattern analysis, DeWiCam is more challenging because it cannot access the encrypted information in the data packets. Yet, DeWiCam overcomes the difficulty and can detect nearby wireless cameras reliably. To further identify whether a camera is in an interested room, we propose a human-assisted identification model. Extension functions of DeWiCam enable the video resolution and audio channel inference to provide further protection. We implement DeWiCam on the Android platform and evaluate it with extensive experiments on 20 cameras. The evaluation results show that DeWiCam can detect cameras with an accuracy of 99% within 2.7 s.

we envision that DeWiCam can be used as follows: when a user enters an untrusted room (e.g., an Airbnb rental), she/ he runs DeWiCam on her/ his smartphone briefly to detect whether a wireless camera is inside the room. Essentially, DeWiCam will automatically analyze wireless traffic to recognize the distinct traffic patterns of wireless cameras, if any, and inform the user of the existence as well as the exact number of wireless cameras.



Figure 1: Hidden wireless cameras cause privacy invasion by remote monitoring. DeWiCam detects wireless cameras over wireless channels using ubiquitous smartphones.



Figure 2: The UI snapshot of DeWiCam. The left figure illustrates the case one camera is detected and the right one shows two cameras are detected in real detection.

Video: Real-time wireless camera detection in a lab.


Publications

Yushi Cheng, Xiaoyu Ji, Tianyang Lu, Wenyuan Xu. DeWiCam: Detecting Hidden Wireless Cameras via Smartphones. ACM Asia Conference on Computer and Communications Security, 2018.