Image Source Identification Using Convolutional Neural Networks in IoT Environment

被引：3
|
作者：
Wang, Yan [1 ]
Sun, Qindong [1 ,2 ]
Rong, Dongzhu [1 ]
Li, Shancang [3 ]
Xu, Li Da [4 ]
机构：
[1] Xian Univ Technol, Shaanxi Key Lab Network Comp & Secur, Xian 710048, Peoples R China
[2] Xian Univ Technol, Sch Cyber Sci & Engn, Xian 710049, Peoples R China
[3] UWE Bristol, Dept Comp Sci, Bristol BS16 1QY, Avon, England
[4] Old Dominion Univ, Dept IT & DS, Norfolk, VA USA
来源：
WIRELESS COMMUNICATIONS & MOBILE COMPUTING | 2021年 / 2021卷
关键词：
CNN;
D O I：
10.1155/2021/5804665
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
引用
收藏
页数：12
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