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Data Hiding in the Wild: Where Computational Intelligence Meets Digital Forensics

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Surveillance in Action

Abstract

In the context of an increasing dependence on multimedia contents, data hiding techniques, such as watermarking and steganography, are becoming more and more important. Due to the complementary nature of their general requirements, i.e., imperceptibility, robustness, security and capacity, many data hiding schemes endeavour to find the optimal performances by applying various approaches inspired from nature. In this paper, we provide a review and analysis of the main computational intelligence approaches, including Artificial Neural Networks (ANNs) and Fuzzy Sets (FSs), which are employed in information hiding. Furthermore, with the aid of the recent state of the art, we discuss the main challenges to be addressed and future directions of research.

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Authors and Affiliations

  1. Agency for Science, Technology and Research, 1 Fusionopolis Way, 487372, Singapore, Singapore

    Victor Pomponiu

  2. Computer Science Department, University of Torino, C. Svizzera 185, CAP 10149, Turin, Italy

    Davide Cavagnino & Marco Botta

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  1. Victor Pomponiu
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  2. Davide Cavagnino
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  3. Marco Botta
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Correspondence to Victor Pomponiu .

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Editors and Affiliations

  1. Department of Informatics and Computers, Hellenic Air Force Academy, Attica, Greece

    Panagiotis Karampelas

  2. Multispectral Imagery Lab, Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, West Virginia, USA

    Thirimachos Bourlai

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Pomponiu, V., Cavagnino, D., Botta, M. (2018). Data Hiding in the Wild: Where Computational Intelligence Meets Digital Forensics. In: Karampelas, P., Bourlai, T. (eds) Surveillance in Action. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-68533-5_15

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