@inproceedings{41c3d68c90354a0e8e666639cb302e6e,
title = "JPEG-phase-aware convolutional neural network for steganalysis of JPEG images",
abstract = "Detection of modern JPEG steganographic algorithms has traditionally relied on features aware of the JPEG phase. In this paper, we port JPEG-phase awareness into the architecture of a convolutional neural network to boost the detection accuracy of such detectors. Another innovative concept introduced into the detector is the {"}catalyst kernel{"} that, together with traditional high-pass filters used to pre-process images allows the network to learn kernels more relevant for detection of stego signal introduced by JPEG steganography. Experiments with J-UNIWARD and UED-JC embedding algorithms are used to demonstrate the merit of the proposed design.",
keywords = "Catalyst kernel, Convolutional neural network, JPEG, Phase aware, Steganalysis, Steganography",
author = "Mo Chen and Vahid Sedighi and Mehdi Boroumand and Jessica Fridrich",
note = "Publisher Copyright: {\textcopyright} 2017 Association for Computing Machinery.; 5th ACM Workshop on Information Hiding and Multimedia Security Workshop, IH and MMSec 2017 ; Conference date: 20-06-2017 Through 22-06-2017",
year = "2017",
month = jun,
day = "20",
doi = "10.1145/3082031.3083248",
language = "English",
series = "IH and MMSec 2017 - Proceedings of the 2017 ACM Workshop on Information Hiding and Multimedia Security",
publisher = "Association for Computing Machinery, Inc",
pages = "75--84",
booktitle = "IH and MMSec 2017 - Proceedings of the 2017 ACM Workshop on Information Hiding and Multimedia Security",
}