Joint Exploitation of Physical-Layer and Artificial Features for Privacy-Preserving Distributed Source Camera Identification

Hui Tian, Haibao Chen (), Yuyan Zhao and Jiawei Zhang
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Hui Tian: School of Computer Science and Technology, Anhui University, Hefei 230601, China
Haibao Chen: School of Computer and Information Engineering, Chuzhou University, Chuzhou 239000, China
Yuyan Zhao: School of Computer and Information Engineering, Chuzhou University, Chuzhou 239000, China
Jiawei Zhang: School of Computer Science and Technology, Anhui University, Hefei 230601, China

Future Internet, 2025, vol. 17, issue 6, 1-24

Abstract: Identifying the source camera of a digital image is a critical task for ensuring image authenticity. In this paper, we propose a novel privacy-preserving distributed source camera identification scheme that jointly exploits both physical-layer fingerprint features and a carefully designed artificial tag. Specifically, we build a hybrid fingerprint model by combining sensor level hardware fingerprints with artificial tag features to characterize the unique identity of the camera in a digital image. To address privacy concerns, the proposed scheme incorporates a privacy-preserving strategy that encrypts not only the hybrid fingerprint parameters, but also the image content itself. Furthermore, within the distributed framework, the identification task performed by a single secondary user is formulated as a binary hypothesis testing problem. Experimental results demonstrated the effectiveness of the proposed scheme in accurately identifying source cameras, particularly under complex conditions such as those involving images processed by social media platforms. Notably, for social media platform identification, our method achieved average accuracy improvements of 7.19% on the Vision dataset and 8.87% on the Forchheim dataset compared to a representative baseline.

Keywords: camera identification; distributed computing; physical layer features; privacy-preserving; hybrid fingerprint model (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2025
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