Entropy Based Data Hiding
A special issue of Entropy (ISSN 1099-4300).
Deadline for manuscript submissions: closed (31 August 2019) | Viewed by 34929
Special Issue Editors
Interests: information security and privacy; copyright protection; multimedia content (digital image, audio and video); watermarking; fingerprinting; steganography; signal processing
Special Issues, Collections and Topics in MDPI journals
Interests: multimedia security; fingerprinting; traitor tracing; signal processing; cryptographic protocol; coding theory; statistical analysis
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
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
Guest Editors
Manuscript Submission Information
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Keywords
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 |
Data Integrity | |
Distortion Measurement | |
Stego signal/Payload |
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