TargetFinder: privacy preserving target search through IoT cameras
TargetFinder: privacy preserving target search through IoT cameras
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DOI：
10.1145/3302505.3310083
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发表时间：
2019-04
期刊：
影响因子：
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通讯作者：
Youssef Khazbak;Junpeng Qiu;Tianxiang Tan;G. Cao
中科院分区：
文献类型：
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作者：
Youssef Khazbak;Junpeng Qiu;Tianxiang Tan;G. Cao
随着物联网摄像头的普及，可以使用众包视频来帮助按需找到感兴趣的目标（例如，犯罪嫌疑人、丢失的孩子、丢失的车辆等）。由于物联网摄像头（如仪表盘摄像头和手机摄像头）无处不在，众包视频与仅使用监控摄像头相比具有更好的空间覆盖范围，从而可以显着提高目标搜索的有效性。然而，当工作人员（物联网摄像头的所有者）提供目标的照片时，这可能会引起隐私问题。此外，工作人员拍摄的视频可能会被滥用来追踪旁观者。为了解决这个问题，我们设计并实现了TargetFinder，这是一个通过物联网摄像头进行目标搜索的隐私保护系统。通过利用同态加密技术，服务器可以在加密信息上搜索目标。我们还提出了一些技术，允许请求者（例如警察）接收包含目标的图像，而不显示所有其他捕获的旁观者图像。此外，目标的面部图像不向服务器和参与工作人员透露。由于加密原语的高计算开销，我们开发了优化技术，以便在移动设备上运行我们的隐私保护协议。一个真实世界的演示和广泛的评估证明了TargetFinder的有效性。
With the proliferation of IoT cameras, it is possible to use crowd-sourced videos to help find interested targets (e.g., crime suspect, lost child, lost vehicle, etc.) on demand. Due to the ubiquity of IoT cameras such as dash mounted cameras and phone camera, the crowdsourced videos have much better spatial coverage compared to only using surveillance cameras, and thus can significantly improve the effectiveness of target search. However, this may raise privacy concerns when workers (owners of IoT cameras) are provided with photos of the target. Also, the videos captured by the workers may be misused to track bystanders. To address this problem, we design and implement TargetFinder, a privacy preserving system for target search through IoT cameras. By exploiting homo-morphic encryption techniques, the server can search for the target on encrypted information. We also propose techniques to allow the requester (e.g., the police) to receive images that include the target, while all other captured images of the bystanders are not revealed. Moreover, the target's face image is not revealed to the server and the participating workers. Due to the high computation overhead of the cryptographic primitives, we develop optimization techniques in order to run our privacy preserving protocol on mobile devices. A real-world demo and extensive evaluations demonstrate the effectiveness of TargetFinder.