MSAI: Masking Sensitive Area of Image on IoT Cameras
Jinqiang Liu Jinqiang Liu, Yining Liu Jinqiang Liu, Lei Cui Yining Liu, Shui Yu · 網際網路技術學刊 · 2021
In smart cities, images captured by Internet of Things (IoT) cameras are transmitted to data center via intermediate nodes. The shared images can reveal much of sensitive information of users, which has caused increasing privacy concerns. Various encryption-based techniques have been developed for privacy preserving. However, they are not suitable for IoT cameras due to the high computation cost. In this paper, we propose a lightweight image privacy protection scheme considering personalized protection requirements of users. We first introduce an object detection algorithm to detect and pick up sensitive areas in images according to the specific requirements of users. Then, we propose a membranebased method to mask the sensitive areas before uploading images to the data center. In particular, the masking operation does not require much computing resources on the used cloud platform, and the masking size of membrane can be dynamically adjusted. Our experiments on real-world datasets demonstrate the effectiveness and feasibility of the proposed scheme.