Digital image forensics is a key branch of digital forensics that based on forensic analysis of image authenticity and image content. The advances in new techniques, such as smart devices, Internet of Things (IoT), artificial images, and social networks, make forensic image analysis play an increasing role in a wide range of criminal case investigation. This work focuses on image source identification by analysing both the fingerprints of digital devices and images in IoT environment. A new convolutional neural network (CNN) method is proposed to identify the source devices that token an image in social IoT environment. The experimental results show that the proposed method can effectively identify the source devices with high accuracy.

中文翻译：

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在物联网环境中使用卷积神经网络进行图像源识别

数字图像取证是数字取证的一个关键分支，它基于对图像真实性和图像内容的取证分析。智能设备、物联网 (IoT)、人工图像和社交网络等新技术的进步，使法医图像分析在广泛的刑事案件调查中发挥着越来越大的作用。这项工作通过分析物联网环境中的数字设备和图像的指纹来专注于图像源识别。提出了一种新的卷积神经网络 (CNN) 方法来识别在社交物联网环境中标记图像的源设备。实验结果表明，所提出的方法可以有效地识别源设备，并且具有较高的准确率。