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Authors: Qingzhong Liu 1 ; Andrew H. Sung 1 ; Mengyu Qiao 1 and Bernardete M. Ribeiro 2

Affiliations: 1 Depart of Computer Science and Institute for Complex Additive Systems Analysis, United States ; 2 University Of Coimbra, Portugal

ISBN: 978-989-8111-66-1

Keyword(s): Steganalysis, JPEG, Image, SVM, Markov, Pattern recognition.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Data Manipulation ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Evolutionary Computing ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Informatics in Control, Automation and Robotics ; Intelligent Control Systems and Optimization ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Symbolic Systems ; Vision and Perception

Abstract: In this paper, we propose a scheme for detecting the information-hiding in multi-class JPEG images by combining expanded Markov process and joint distribution features. First, the features of the condition and joint distributions in the transform domains are extracted (including the Discrete Cosine Transform or DCT, the Discrete Wavelet Transform or DWT); next, the same features from the calibrated version of the testing images are extracted. A Support Vector Machine (SVM) is applied to the differences of the features extracted from the testing image and from the calibrated version. Experimental results show that this approach delivers good performance in identifying several hiding systems in JPEG images.

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Paper citation in several formats:
Liu Q.; H. Sung A.; Qiao M.; Ribeiro B. and (2009). USING EXPANDED MARKOV PROCESS AND JOINT DISTRIBUTION FEATURES FOR JPEG STEGANALYSIS.In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-8111-66-1, pages 226-231. DOI: 10.5220/0001658402260231

@conference{icaart09,
author={Qingzhong Liu and Andrew {H. Sung} and Mengyu Qiao and Bernardete M. Ribeiro},
title={USING EXPANDED MARKOV PROCESS AND JOINT DISTRIBUTION FEATURES FOR JPEG STEGANALYSIS},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2009},
pages={226-231},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001658402260231},
isbn={978-989-8111-66-1},
}

TY - CONF

JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - USING EXPANDED MARKOV PROCESS AND JOINT DISTRIBUTION FEATURES FOR JPEG STEGANALYSIS
SN - 978-989-8111-66-1
AU - Liu, Q.
AU - H. Sung, A.
AU - Qiao, M.
AU - Ribeiro, B.
PY - 2009
SP - 226
EP - 231
DO - 10.5220/0001658402260231

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