Compact Representation of Digital Camera's Fingerprint with Convolutional Autoencoder

Jarosław Bernacki, Rafał Scherer

2024

Abstract

In this paper, we address the challenge of digital camera identification within the realm of digital forensics. While numerous algorithms leveraging camera fingerprints exist, few offer both speed and accuracy, particularly in the context of modern high-resolution digital cameras. Moreover, the storage requirements for these fingerprints, often represented as matrices corresponding to the original image dimensions, pose practical challenges for forensic centers. To tackle these issues, we propose a novel approach utilizing a convolutional autoencoder (AE) to generate compact representations of camera fingerprints. Our method aims to balance accuracy with efficiency, facilitating rapid and reliable identification across a range of cameras and image types. Extensive experimental evaluation demonstrates the effectiveness of our approach, showcasing its potential for practical deployment in forensic scenarios. By providing a streamlined method for camera identification, our work contributes to advancing the capabilities of digital forensic analysis.

Paper Citation

in Harvard Style

Bernacki J. and Scherer R. (2024). Compact Representation of Digital Camera's Fingerprint with Convolutional Autoencoder. In Proceedings of the 21st International Conference on Security and Cryptography - Volume 1: SECRYPT; ISBN 978-989-758-709-2, SciTePress, pages 792-797. DOI: 10.5220/0012821300003767

in Bibtex Style

@conference{secrypt24,
author={Jarosław Bernacki and Rafał Scherer},
title={Compact Representation of Digital Camera's Fingerprint with Convolutional Autoencoder},
booktitle={Proceedings of the 21st International Conference on Security and Cryptography - Volume 1: SECRYPT},
year={2024},
pages={792-797},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012821300003767},
isbn={978-989-758-709-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 21st International Conference on Security and Cryptography - Volume 1: SECRYPT
TI - Compact Representation of Digital Camera's Fingerprint with Convolutional Autoencoder
SN - 978-989-758-709-2
AU - Bernacki J.
AU - Scherer R.
PY - 2024
SP - 792
EP - 797
DO - 10.5220/0012821300003767
PB - SciTePress