Image Source Identification Using Convolutional Neural Networks in IoT Environment

Author:

Wang Yan1,Sun Qindong12ORCID,Rong Dongzhu1,Li Shancang3,Xu Li Da4

Affiliation:

1. Shaanxi Key Laboratory of Network Computing and Security, Xi’an University of Technology, 710048, China

2. School of Cyber Science and Engineering, Xi’an Jiaotong University, 710049, China

3. Department of Computer Science, UWE Bristol, BS16 1QY, UK

4. Department of IT and DS, Old Dominion University, Norfolk, VA, USA

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.

Funder

Youth Innovation Team of Shaanxi Universities

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems

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