Information Hiding and Coding Theory
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".
Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 13221
Special Issue Editors
Interests: quantum computing; cryptography; sequences for communications and security; coding theory
Special Issue Information
Dear Colleagues,
Information hiding technologies such as steganography and watermarking have played important roles in multimedia security and services over the last fifty years. In the last decade, alongside the proliferation of the Internet technologies, information hiding has been increasingly used to provide specialized security guarantees to medical records of scans, X-rays, and reports. The use of information hiding technologies in commercial applications is becoming more popular due to the extraordinary unique special security features they provide to the domain, which are otherwise difficult or expensive to realize using regular methods. The coding theory, which was initially developed to solve errors in communication channels can achieve information hiding primitives. When used in information hiding applications, custom specific coding and decoding techniques are required. Furthermore, the choice of hiding techniques must respect the domain-specific needs of the multimedia application and, accordingly, techniques from machine learning are required to support their use in actual practice.
We intend for this Special Issue to serve as a forum for the presentation of novel and improved techniques for information hiding and coding theory in modern commercial multimedia and medical technologies. Relevant topics include novel coding and decoding techniques in conjunction with appropriate signal processing of the relevant multimedia cover data. Our focus is on both fundamental and application-specific analyses of modern information hiding techniques using machine learning and other statistical analysis techniques using information theory.
We invite authors to submit previously unpublished contributions in any area related to information hiding and coding including, but not limited to, the following subtopics:
- Theory of information hiding;
- Coding and decoding for information hiding;
- Embedding functions for information hiding;
- Signal processing for information hiding;
- Spread spectrum-based information hiding;
- Watermarking;
- Covert communications;
- Fingerprinting codes;
- Machine learning and information hiding;
- Deep steganography (extension of machine learning with steganography);
- Steganographic data security for virtual healthcare (relevant to COVID-19 as the use of telehealth has become more pronounced and could remain this way for 3 to 5 years).
Prof. Dr. Udaya Parampalli
Prof. Dr. Tetsuya Kojima
Guest Editors
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 submissions that pass pre-check are 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 2600 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.
Keywords
- information hiding
- watermarking
- spread spectrum steganography
- coding and decoding for watermarking
- machine learning for information hiding processing
