Document Type
Article
Publication Date
2021
DOI
10.1155/2021/5804665
Publication Title
Wireless Communications and Mobile Computing
Volume
2021
Pages
5804665 (1-12)
Abstract
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.
Original Publication Citation
Wang, Y., Sun, Q., Rong, D., Li, S., & Xu, L. D. (2021). Image source identification using convolutional neural networks in IoT environment. Wireless Communications and Mobile Computing, 2021, 1-12, Article 5804665. https://doi.org/10.1155/2021/5804665
Repository Citation
Wang, Yan; Sun, Qindong; Rong, Dongzhu; Li, Shancang; and Xu, Li Da, "Image Source Identification Using Convolutional Neural Networks in IoT Environment" (2021). Information Technology & Decision Sciences Faculty Publications. 57.
https://digitalcommons.odu.edu/itds_facpubs/57
Included in
Criminology Commons, OS and Networks Commons, Social Media Commons, Technology and Innovation Commons
Comments
© 2021 Yan Wang et al.
This is an open access article distributed under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.