Special Issue "Entropy Based Data Hiding"
A special issue of Entropy (ISSN 1099-4300).
Deadline for manuscript submissions: 31 May 2019
Dr. David Megías Jiménez
Internet Interdisciplinary Institute (IN3), Universitat Oberta de Catalunya, Parc Mediterrani de la Tecnologia (edifici B3), Av. Carl Friedrich Gauss, 5, 08860, Castelldefels, Spain
Website | E-Mail
Interests: Information security and privacy; copyright protection; multimedia content (digital image, audio and video); watermarking; fingerprinting; steganography; signal processing
Data hiding techniques have been widely used to provide copyright protection, data integrity, covert communication, non-repudiation, and authentication, among other applications. In the context of an increased dissemination and distribution of multimedia content (text, audio, video, etc.) over the Internet, data hiding methods, such as digital watermarking and steganography, are becoming more and more important in providing multimedia security. Due to the complimentary nature of general requirements of these methods, i.e., imperceptibility, robustness, security and capacity, many data hiding schemes attempt to find optimal performance by applying concepts of information theory, such as entropy. Entropy has been used extensively to support data hiding algorithms. Examples include the use of information entropy as a “masking effect” of Just Noticeable Difference (JND) model in digital watermarking systems to obtain a better trade-off between imperceptibility and robustness; as a measure to evaluate the complexity of cover object to achieve Bit Error Rate (BER) constraint in steganographic schemes; as a criterion to determine the embedding positions in the cover data so as to cause minimal perceptual distortion; and as a measure to evaluate information leakage in the embedding process.
The goal of this Special Issue is to concentrate on (but not limited to) the improvement of data hiding algorithms through information entropy, and on the application of entropy in real-world data hiding techniques. It will bring together researchers and practitioners from different research fields including data hiding, signal processing, cryptography or information theory, among others, to contribute with original research outcomes that address issues in data hiding algorithms using information theory approaches.
Dr. David Megías Jiménez
Dr. Minoru Kuribayashi
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
|Specific Keywords||Generic Keywords|
|Entropy-based audio/video/image Steganalysis||Steganalysis|
|Entropy-based audio/video/image Steganography||Steganography|
|Entropy-based audio/video/image Watermarking||Digital Watermarking|
|Coverless Data Hiding||Digital Fingerprinting|
|Reversible Data Hiding and Applications||Entropy|
|Forensic Aspects of Data Hiding||Traitor-Tracing|
|Blind Detection/Extraction||Ownership Proof/Copyright Protection|
|Visual Cryptography||Transform Coding|
|Embedding Capacity||Data Segmentation|
|Signal Processing||Embedding Capacity|
|Emerging Applications of Data Hiding in IoT and Big Data||Extraction/Detection|